A Deep Learning-Based Rotten Food Recognition App for Older Adults: Development and Usability Study.

BACKGROUND: Older adults are at greater risk of eating rotten fruits and of getting food poisoning because cognitive function declines as they age, making it difficult to distinguish rotten fruits. To address this problem, researchers have developed and evaluated various tools to detect rotten food items in various ways. Nevertheless, little is known about how to create an app to detect rotten food items to support older adults at a risk of health problems from eating rotten food items. OBJECTIVE: This study aimed to (1) create a smartphone app that enables older adults to take a picture of food items with a camera and classifies the fruit as rotten or not rotten for older adults and (2) evaluate the usability of the app and the perceptions of older adults about the app. METHODS: We developed a smartphone app that supports older adults in determining whether the 3 fruits selected for this study (apple, banana, and orange) were fresh enough to eat. We used several residual deep networks to check whether the fruit photos collected were of fresh fruit. We recruited healthy older adults aged over 65 years (n=15, 57.7%, males and n=11, 42.3%, females) as participants. We evaluated the usability of the app and the participants' perceptions about the app through surveys and interviews. We analyzed the survey responses, including an after-scenario questionnaire, as evaluation indicators of the usability of the app and collected qualitative data from the interviewees for in-depth analysis of the survey responses. RESULTS: The participants were satisfied with using an app to determine whether a fruit is fresh by taking a picture of the fruit but are reluctant to use the paid version of the app. The survey results revealed that the participants tended to use the app efficiently to take pictures of fruits and determine their freshness. The qualitative data analysis on app usability and participants' perceptions about the app revealed that they found the app simple and easy to use, they had no difficulty taking pictures, and they found the app interface visually satisfactory. CONCLUSIONS: This study suggests the possibility of developing an app that supports older adults in identifying rotten food items effectively and efficiently. Future work to make the app distinguish the freshness of various food items other than the 3 fruits selected still remains.

Associations between brachial-ankle pulse wave velocity and hypertensive retinopathy in treated hypertensive adults: Results from the China Stroke Primary Prevention Trial (CSPPT).

Although the association between persistent hypertension and the compromise of both micro- and macro-circulatory functions is well recognized, a significant gap in quantitative investigations exploring the interplay between microvascular and macrovascular injuries still exists. In this study, the authors looked into the relationship between brachial-ankle pulse wave velocity (baPWV) and hypertensive retinopathy in treated hypertensive adults. The authors conducted a cross-sectional study of treated hypertensive patients with the last follow-up data from the China Stoke Primary Prevention Trial (CSPPT) in 2013. With the use of PWV/ABI instruments, baPWV was automatically measured. The Keith-Wagener-Barker classification was used to determine the diagnosis of hypertensive retinopathy. The odds ratio (OR) and 95% confidence interval (CI) for the connection between baPWV and hypertensive retinopathy were determined using multivariable logistic regression models. The OR curves were created using a multivariable-adjusted restricted cubic spline model to investigate any potential non-linear dose-response relationships between baPWV and hypertensive retinopathy. A total of 8514 (75.5%) of 11,279 participants were diagnosed with hypertensive retinopathy. The prevalence of hypertensive retinopathy increased from the bottom quartile of baPWV to the top quartile: quartile 1: 70.7%, quartile 2: 76.1%, quartile 3: 76.7%, quartile 4: 78.4%. After adjusting for potential confounders, baPWV was positively associated with hypertensive retinopathy (OR = 1.05, 95% CI, 1.03-1.07, p < .001). Compared to those in the lowest baPWV quartile, those in the highest baPWV quartile had an odds ratio for hypertensive retinopathy of 1.61 (OR = 1.61, 95% CI: 1.37-1.89, p < .001). Two-piece-wise logistic regression model demonstrated a nonlinear relationship between baPWV and hypertensive retinopathy with an inflection point of 17.1 m/s above which the effect was saturated .

Interoceptive posture awareness and accuracy: a novel photographic strategy towards making posture actionable.

Interoception, sometimes referred to as the 'hidden sense,' communicates the state of internal conditions for autonomic energy regulation and is important for human motor control as well as self-awareness. The insula, the cortex of interoception, integrates internal senses such as hunger, thirst and emotions. With input from the cerebellum and proprioceptive inputs, it creates a vast sensorimotor network essential for static posture and dynamic movement. With humans being bipedal to allow for improved mobility and energy utilization, greater neuromotor control is required to effectively stabilize and control the four postural zones of mass (i.e., head, torso, pelvis, and lower extremities) over the base of support. In a dynamic state, this neuromotor control that maintains verticality is critical, challenging energy management for somatic motor control as well as visceral and autonomic functions. In this perspective article, the authors promote a simple series of posture photographs to allow one to integrate more accurate alignment of their postural zones of mass with respect to the gravity line by correlating cortical interoception with cognitive feedback. Doing this focuses one on their body perception in space compared to the objective images. Strengthening interoceptive postural awareness can shift the net result of each zone of postural mass during day-to-day movement towards stronger posture biomechanics and can serve as an individualized strategy to optimize function, longevity, and rehabilitation.

Tailored Prompting to Improve Adherence to Image-Based Dietary Assessment: Mixed Methods Study.

Background: Accurately assessing an individual's diet is vital in the management of personal nutrition and in the study of the effect of diet on health. Despite its importance, the tools available for dietary assessment remain either too imprecise, expensive, or burdensome for clinical or research use. Image-based methods offer a potential new tool to improve the reliability and accessibility of dietary assessment. Though promising, image-based methods are sensitive to adherence, as images cannot be captured from meals that have already been consumed. Adherence to image-based methods may be improved with appropriately timed prompting via text message. Objective: This study aimed to quantitatively examine the effect of prompt timing on adherence to an image-based dietary record and qualitatively explore the participant experience of dietary assessment in order to inform the design of a novel image-based dietary assessment tool. Methods: This study used a randomized crossover design to examine the intraindividual effect of 3 prompt settings on the number of images captured in an image-based dietary record. The prompt settings were control, where no prompts were sent; standard, where prompts were sent at 7:15 AM, 11:15 AM, and 5:15 PM for every participant; and tailored, where prompt timing was tailored to habitual meal times for each participant. Participants completed a text-based dietary record at baseline to determine the timing of tailored prompts. Participants were randomized to 1 of 6 study sequences, each with a unique order of the 3 prompt settings, with each 3-day image-based dietary record separated by a washout period of at least 7 days. The qualitative component comprised semistructured interviews and questionnaires exploring the experience of dietary assessment. Results: A total of 37 people were recruited, and 30 participants (11 male, 19 female; mean age 30, SD 10.8 years), completed all image-based dietary records. The image rate increased by 0.83 images per day in the standard setting compared to control (P=.23) and increased by 1.78 images per day in the tailored setting compared to control (P≤.001). We found that 13/21 (62%) of participants preferred to use the image-based dietary record versus the text-based dietary record but reported method-specific challenges with each method, particularly the inability to record via an image after a meal had been consumed. Conclusions: Tailored prompting improves adherence to image-based dietary assessment. Future image-based dietary assessment tools should use tailored prompting and offer both image-based and written input options to improve record completeness.

A new segmentation algorithm for peripapillary atrophy and optic disk from ultra-widefield Photographs1.

BACKGROUND AND OBJECTIVE: The prevalence of myopia and high myopia is increasing globally, underscoring the growing importance of diagnosing high myopia-related pathologies. While existing image segmentation models, such as U-Net, UNet++, ResU-Net, and TransUNet, have achieved significant success in medical image segmentation, they still face challenges when dealing with ultra-widefield (UWF) fundus images. This study introduces a novel automatic segmentation algorithm for the optic disc and peripapillary atrophy (PPA) based on UWF fundus images, aimed at assisting ophthalmologists in more accurately diagnosing high myopia-related diseases. METHODS: In this study, we developed a segmentation model leveraging a Transformer-based network structure, complemented by atrous convolution and selective boundary aggregation modules, to elevate the accuracy of segmenting the optic disc and PPA in UWF photography. The atrous convolution module adeptly manages multi-scale features, catering to the variances in target sizes and expanding the deep network's receptive field. Concurrently, the incorporation of the selective boundary aggregation module in the skip connections of the model significantly improves the differentiation of boundary information between segmentation targets. Moreover, the comparison of our proposed algorithm with classical segmentation models like U-Net, UNet++, ResU-Net, and TransUNet highlights its considerable advantages in processing UWF photographs. RESULTS: The experimental results show that, compared to the other four models, our algorithm demonstrates substantial improvements in segmenting the optic disc and PPA in UWF photographs. In PPA segmentation, our algorithm improves by 0.8% in Dice, 1.8% in sensitivity, and 1.3% in intersection over union (IOU). In optic disc segmentation, our algorithm improves by 0.3% in Dice, 0.6% in precision, and 0.4% in IOU. CONCLUSION: Our proposed method improves the segmentation accuracy of PPA and optic disks based on UWF photographs, which is valuable for diagnosing high myopia-related diseases in ophthalmology clinics.

Oral Cannabidiol for Seborrheic Dermatitis in Patients With Parkinson Disease: Randomized Clinical Trial.

BACKGROUND: Seborrheic dermatitis (SD) affects 18.6%-59% of persons with Parkinson disease (PD), and recent studies provide evidence that oral cannabidiol (CBD) therapy could reduce sebum production in addition to improving motor and psychiatric symptoms in PD. Therefore, oral CBD could be useful for improving symptoms of both commonly co-occurring conditions. OBJECTIVE: This study investigates whether oral CBD therapy is associated with a decrease in SD severity in PD. METHODS: Facial photographs were collected as a component of a randomized (1:1 CBD vs placebo), parallel, double-blind, placebo-controlled trial assessing the efficacy of a short-term 2.5 mg per kg per day oral sesame solution CBD-rich cannabis extract (formulated to 100 mg/mL CBD and 3.3 mg/mL THC) for reducing motor symptoms in PD. Participants took 1.25 mg per kg per day each morning for 4 ±1 days and then twice daily for 10 ±4 days. Reviewers analyzed the photographs independently and provided a severity ranking based on the Seborrheic Dermatitis Area and Severity Index (SEDASI) scale. Baseline demographic and disease characteristics, as well as posttreatment SEDASI averages and the presence of SD, were analyzed with 2-tailed t tests and Pearson χ2 tests. SEDASI was analyzed with longitudinal regression, and SD was analyzed with generalized estimating equations. RESULTS: A total of 27 participants received a placebo and 26 received CBD for 16 days. SD severity was low in both groups at baseline, and there was no treatment effect. The risk ratio for patients receiving CBD, post versus pre, was 0.69 (95% CI 0.41-1.18; P=.15), compared to 1.20 (95% CI 0.88-1.65; P=.26) for the patients receiving the placebo. The within-group pre-post change was not statistically significant for either group, but they differed from each other (P=.07) because there was an estimated improvement for the CBD group and an estimated worsening for the placebo group. CONCLUSIONS: This study does not provide solid evidence that oral CBD therapy reduces the presence of SD among patients with PD. While this study was sufficiently powered to detect the primary outcome (efficacy of CBD on PD motor symptoms), it was underpowered for the secondary outcomes of detecting changes in the presence and severity of SD. Multiple mechanisms exist through which CBD can exert beneficial effects on SD pathogenesis. Larger studies, including participants with increased disease severity and longer treatment periods, may better elucidate treatment effects and are needed to determine CBD's true efficacy for affecting SD severity. TRIAL REGISTRATION: ClinicalTrials.gov NCT03582137; https://clinicaltrials.gov/ct2/show/NCT03582137.

Influence of education level and gender of dental students on perception of dental aesthetics.

BACKGROUND: Fulfilling aesthetic norms is an imperative of modern society. Accordingly, aesthetics has found its important role in dental medicine. The aim was to study whether there is a difference in the perception of tooth shade change and anatomical variations of anterior maxillary teeth among dental students depending on the level of education, gender, and experience in assisting in a dental office. METHODS: The research was conducted among dental students via the Google Forms platform. Students evaluated the aesthetic acceptability of a smile on the unaltered, reference photograph (RP) and on the other 28 photographs in which the tooth shade (lighter and darker teeth), length (shortened central incisors, elongated, and beveled lateral incisors, elongated canines) and position (atypical and typical rotations and diastemas) of the upper maxillary teeth were altered by digital manipulation. The 1-10 assessment scale was used. Statistical analysis comprised one-way Kolmogorov-Smirnov test, X2 tests, t-test, and 3-way MANOVA. RESULTS: In the research 208 students participated, 113 were preclinical students, 104 assisted in dental office and 175 were females. There were no significant effects of gender regarding length and position modifications (p > .05), while women were stricter in evaluation of lighter shade (p < .05). Clinical students were stricter in evaluating all manipulated photographs (MP) except those towards darker shade modifications, while assisting in a dental office or having a dentist in close family showed no significant effects (p > .05). CONCLUSIONS: With a higher level of targeted academic education, dental students sharpen their ability to notice deviations from the aesthetic norms of a smile.

Using AI Text-to-Image Generation to Create Novel Illustrations for Medical Education: Current Limitations as Illustrated by Hypothyroidism and Horner Syndrome.

Our research letter investigates the potential, as well as the current limitations, of widely available text-to-image tools in generating images for medical education. We focused on illustrations of important physical signs in the face (for which confidentiality issues in conventional patient photograph use may be a particular concern) that medics should know about, and we used facial images of hypothyroidism and Horner syndrome as examples.

Deep Learning Models for the Screening of Cognitive Impairment Using Multimodal Fundus Images.

OBJECTIVE: We aimed to develop a deep learning system capable of identifying subjects with cognitive impairment quickly and easily based on multimodal ocular images. DESIGN: Cross sectional study. SUBJECTS: Participants of Beijing Eye Study 2011 and patients attending Beijing Tongren Eye Center and Beijing Tongren Hospital Physical Examination Center. METHODS: We trained and validated a deep learning algorithm to assess cognitive impairment using retrospectively collected data from the Beijing Eye Study 2011. Cognitive impairment was defined as a Mini-Mental State Examination score < 24. Based on fundus photographs and OCT images, we developed 5 models based on the following sets of images: macula-centered fundus photographs, optic disc-centered fundus photographs, fundus photographs of both fields, OCT images, and fundus photographs of both fields with OCT (multimodal). The performance of the models was evaluated and compared in an external validation data set, which was collected from patients attending Beijing Tongren Eye Center and Beijing Tongren Hospital Physical Examination Center. MAIN OUTCOME MEASURES: Area under the curve (AUC). RESULTS: A total of 9424 retinal photographs and 4712 OCT images were used to develop the model. The external validation sets from each center included 1180 fundus photographs and 590 OCT images. Model comparison revealed that the multimodal performed best, achieving an AUC of 0.820 in the internal validation set, 0.786 in external validation set 1, and 0.784 in external validation set 2. We evaluated the performance of the multi-model in different sexes and different age groups; there were no significant differences. The heatmap analysis showed that signals around the optic disc in fundus photographs and the retina and choroid around the macular and optic disc regions in OCT images were used by the multimodal to identify participants with cognitive impairment. CONCLUSIONS: Fundus photographs and OCT can provide valuable information on cognitive function. Multimodal models provide richer information compared with single-mode models. Deep learning algorithms based on multimodal retinal images may be capable of screening cognitive impairment. This technique has potential value for broader implementation in community-based screening or clinic settings. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The Agreement between Consumer-Driven Self-Assessment of Psoriasis Severity and Physician-Assessed Severity Based on Patient-Taken Photographs Is Weak: A Cross-Sectional Study.

INTRODUCTION: Digital advancements have given access to huge amounts of real-world data (RWD) widely used for dermatological research. OBJECTIVES: The objective of this study was to investigate the agreement between consumer-driven self-assessed psoriasis severity and physician-assessed severity based on photographs. METHODS: Customer IDs in the NØIE database (Danish skincare company) from 2009 to 2022 with a smartphone photograph of psoriasis vulgaris on the body and a corresponding completed questionnaire were included. Smartphone photographs were evaluated by a physician-assessing erythema, induration, and scaling on a scale from 0 to 4 based on Psoriasis Area Severity Index (PASI). Self-assessment was done on a scale from 0 to 10 and converted to 0-4 scale (0 converted to 0; 1-3 to 1; 4-6 to 2; 7-8 to 3; and 9-10 to 4). Intraclass correlation coefficients with 95% confidence intervals (CIs) were calculated. RESULTS: In total, 187 patients (63% women) with mean age of 38 years were included. Self-assessment scores were higher than physicians' assessment scores for all groups, and scaling was closest to the physicians' assessment, while erythema and induration had a greater distance between the physicians' and patients' assessment. The correlation between self-assessed and physician-assessed psoriasis severity for all patients was 0.23 (95% CI: 0.0-0.92); 0.34 (95% CI: 0.0-0.95) for chronic patients; and 0.09 (-0.01 to 0.82) for non-chronic patients. The agreement was better for men (0.53 [-0.02 to 0.98]) than for women (0.12 [-0.01 to 0.84]). CONCLUSION: There was weak agreement between self-assessed psoriasis severity and photographically assessed severity by the physician. Consumer-driven RWD should be interpreted with caution.

Photographs in burn patient diaries: A qualitative study of patients' and nurses' experiences.

OBJECTIVE: To explore burn patients' and burn intensive care nurses' experiences of the photos in patient diaries. DESIGN: A qualitative inductive study using thematic analysis was performed. We conducted individual interviews with six former burn patients (age range 20-77 years; four women), and two focus groups with 11 burn intensive care nurses (age range 38-61 years; all women). Data from patients and nurses were analysed together, and the findings reported according to the consolidated criteria for reporting qualitative research (COREQ). SETTING: A Norwegian burn centre where the writing of diaries including text and photos has been practiced for approximately two decades. FINDINGS: Three main themes were derived from the combined analysis of the two data sets: hesitating when facing photos; visualising others care; and visualising the trajectory from burn trauma to recovery. Although the patients worried beforehand about what they would see in the photos and the nurses feared to select frightening photos, the photos were welcome, and several patients said they would have liked even more. The photos filled in gaps of memory, told more than words, and did not lie. Photos of family, friends or staff demonstrated shared actions that supported memories and recovery. CONCLUSION: Both the burn patients and the burn intensive care nurses considered photos to be an essential part of the diary that gave context and provided a factual presentation of the patients' pathway of treatment, care and recovery. IMPLICATION FOR CLINICAL PRACTICE: Tailored information about photo content should be offered to patients before a diary is handed over to them. Nurses should attempt to include photos covering the patients' entire stay at the burn centre, as well as photos of family, friends and staff. Individual nurses should be supported in their practical selection of photos for the diary.

The Critical Photographic Variables Contributing to Skull-Face Superimposition Methods to Assist Forensic Identification of Skeletons: A Review.

When an unidentified skeleton is discovered, a video superimposition (VS) of the skull and a facial photograph may be undertaken to assist identification. In the first instance, the method is fundamentally a photographic one, requiring the overlay of two 2D photographic images at transparency for comparison. Presently, mathematical and anatomical techniques used to compare skull/face anatomy dominate superimposition discussions, however, little attention has been paid to the equally fundamental photographic prerequisites that underpin these methods. This predisposes error, as the optical parameters of the two comparison photographs are (presently) rarely matched prior to, or for, comparison. In this paper, we: (1) review the basic but critical photographic prerequisites that apply to VS; (2) propose a replacement for the current anatomy-centric searches for the correct 'skull pose' with a photographic-centric camera vantage point search; and (3) demarcate superimposition as a clear two-stage phased procedure that depends first on photographic parameter matching, as a prerequisite to undertaking any anatomical comparison(s).

Frailty assessment using photographs in patients undergoing transcatheter aortic valve replacement.

BACKGROUND: When frailty is considered in patient selection, better outcomes are achieved in transcatheter aortic valve replacement (TAVR) procedures. This study investigated whether patient photographs could be utilized to qualitatively assess patient frailty and independently predict poor outcomes following TAVR. METHODS: This study included 1345 patients with severe aortic stenosis who underwent TAVR at the Sakakibara Heart Institute, Japan, between 2013 and 2022. Patient photographs were taken prior to the initial outpatient clinic examination or at discharge in case the patient's first visit was unplanned admission. Frailty was assessed from patient photographs using a four-point photographic frailty scale; 1 (non-frail), 2 (vulnerable), 3 (mild frail), and 4 (frail). Photographic frailty scale of 3 and 4 were defined as high. The primary endpoint was all-cause mortality following TAVR. RESULTS: Seven hundred ninety-six patients who had their facial photographs taken within six months before the TAVR procedure were analyzed. Patients with a higher photographic frailty scale belonged to New York Heart Association classes III/IV, and had higher Society of Thoracic Surgeons scores, higher incidence of wheelchair usage, lower hemoglobin, and smaller aortic valve areas. According to the frailty assessment, patients with a higher photographic frailty scale exhibited slower performance in the 5-m walk test, reduced hand grip strength, more severe dementia, had a higher clinical frailty scale, and lower serum albumin level. Multivariable Cox regression analysis revealed that the high photographic frailty scale was independently associated with all-cause mortality (adjusted hazard ratio 1.62, 95 % confidence interval 1.12-2.33, p = 0.010). Kaplan-Meier analysis indicated that patients with high photographic frailty scale had higher all-cause mortality rates compared to those with low scale (log-rank p = 0.011). CONCLUSIONS: Patient registration photographs can be used to obtain qualitative assessments of frailty in severe aortic stenosis cases, and such assessments can independently predict poor outcomes following TAVR.

AI-based dental caries and tooth number detection in intraoral photos: Model development and performance evaluation.

OBJECTIVES: In this study, we aimed to integrate tooth number recognition and caries detection in full intraoral photographic images using a cascade region-based deep convolutional neural network (R-CNN) model to facilitate the practical application of artificial intelligence (AI)-driven automatic caries detection in clinical practice. METHODS: Our dataset comprised 24,578 images, encompassing 4787 upper occlusal, 4347 lower occlusal, 5230 right lateral, 5010 left lateral, and 5204 frontal views. In each intraoral image, tooth numbers and, when present, dental caries, including their location and stage, were annotated using bounding boxes. A cascade R-CNN model was used for dental caries detection and tooth number recognition within intraoral images. RESULTS: For tooth number recognition, the model achieved an average mean average precision (mAP) score of 0.880. In the task of dental caries detection, the model's average mAP score was 0.769, with individual scores spanning from 0.695 to 0.893. CONCLUSIONS: The primary objective of integrating tooth number recognition and caries detection within full intraoral photographic images has been achieved by our deep learning model. The model's training on comprehensive intraoral datasets has demonstrated its potential for seamless clinical application. CLINICAL SIGNIFICANCE: This research holds clinical significance by achieving AI-driven automatic integration of tooth number recognition and caries detection in full intraoral images where multiple teeth are visible. It has the potential to promote the practical application of AI in real-life and clinical settings.

A Case of Pigmented Paravenous Retinochoroidal Atrophy With Retinitis Pigmentosa.

Chorioretinal atrophy with pigmentation along the retinal veins was observed in the right fundus of a 49-year-old patient. Extensive retinitis pigmentosa (RP) was observed in the left eye. Dynamic quantitative visual field testing revealed a scotoma in the right eye that corresponded to the area of ​​retinochoroidal atrophy and afferent visual field constriction was observed on the left eye. An electroretinogram test revealed that the right eye showed attenuated type and the left eye showed negative type. Thus, the conditions of his right eye and left eye were diagnosed as pigmented paravenous retinochoroidal atrophy (PPRCA) and RP, respectively. Thus, there may be a higher proportion of PPRCA patients with unilateral RP than expected.

[Adolescents' Experiences of Non-Suicidal Self-Injury: An Interpretative Phenomenological Analysis Stud].

PURPOSE: This qualitative study used interpretative phenomenological analysis and photovoice methods to explore the meaning of non-suicidal self-injury experienced by adolescents. METHODS: Participants were adolescents enrolled in middle and high schools in Gyeonggi-do and Jeollabuk-do who were selected through snowball sampling. Six participants had repeatedly engaged in self-injurious behavior for over a year. Data were collected through in-depth interviews and the photovoice method between November 2020 and July 2021. The collected data were analyzed using six steps of interpretative phenomenological analysis. RESULTS: The results yielded 5 main themes and 18 subthemes. The main themes were 'a silent cry to an indifferent world', 'a heartache that one endures with scars', 'an inescapable cycle', 'filling the space in one's heart', and 'healing the wounds'. The study findings revealed that the self-injurious behavior of adolescents began as a consequence of feeling lost and struggling with conflicts at home and school, which helped them relieve tension and pain. Nonetheless, inflicting self-injury only left signs of regret and remorse, which became a trace that the participants wanted to hide. However, the wounds healed after receiving attention and support from others. They were determined to stop engaging in repeated self-injurious behaviors and made efforts to do so. CONCLUSION: This study can be used as a basis for the development of educational programs to prevent non-suicidal self-injury in adolescents. Additionally, it can inform nursing interventions that focus on building support systems to help adolescents who attempt self-injury.

Assessing the Impact of Image Quality on Deep Learning Classification of Infectious Keratitis.

Objective: To investigate the impact of corneal photograph quality on convolutional neural network (CNN) predictions. Design: A CNN trained to classify bacterial and fungal keratitis was evaluated using photographs of ulcers labeled according to 5 corneal image quality parameters: eccentric gaze direction, abnormal eyelid position, over/under-exposure, inadequate focus, and malpositioned light reflection. Participants: All eligible subjects with culture and stain-proven bacterial and/or fungal ulcers presenting to Aravind Eye Hospital in Madurai, India, between January 1, 2021 and December 31, 2021. Methods: Convolutional neural network classification performance was compared for each quality parameter, and gradient class activation heatmaps were generated to visualize regions of highest influence on CNN predictions. Main Outcome Measures: Area under the receiver operating characteristic and precision recall curves were calculated to quantify model performance. Bootstrapped confidence intervals were used for statistical comparisons. Logistic loss was calculated to measure individual prediction accuracy. Results: Individual presence of either light reflection or eyelids obscuring the corneal surface was associated with significantly higher CNN performance. No other quality parameter significantly influenced CNN performance. Qualitative review of gradient class activation heatmaps generally revealed the infiltrate as having the highest diagnostic relevance. Conclusions: The CNN demonstrated expert-level performance regardless of image quality. Future studies may investigate use of smartphone cameras and image sets with greater variance in image quality to further explore the influence of these parameters on model performance. Financial Disclosures: Proprietary or commercial disclosure may be found after the references.

Use of digital retinography to detect vascular changes in pre-diabetic patients: a cross-sectional study.

BACKGROUND: Diabetic retinopathy (DR) is a common complication of DM and may go unnoticed until irreversible damage occurs. Its screening can contribute to the early detection. Although, there are no studies which investigate the ability of digital retinography to detect vascular changes in pre-diabetic patients. OBJECTIVE: Identify the prevalence and severity of RD in patients with pre-diabetes. METHODS: Cross-sectionalstudy carried out in a sample of patients with pre-diabetes and weight excess characterized from January 2020 to April 2023. Sociodemographic and clinical variables were collected, in addition to lifestyle habits. Retinographic evaluation was also performed using a Digital Retinography. For the analysis of all variables, the adopted significance level was 5%. The software used for the analysis was SPSS version 25.0. RESULTS: Of 108 patients selected 7.1% have alteration in the exam indicating DR. Among the participants with diabetic retinopathy, four had the moderate form (50%), three the moderate form (37%) and only one participant had the severe form (13%). CONCLUSIONS: Our findings highlight the importance of preventive measures and adequate control of these conditions in pre-diabetic patients, in order to prevent or delay the progression of diabetic retinopathy and, consequently, reduce the risk of blindness and other ocular complications.

Pivotal trial of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from CMERC-HI.

OBJECTIVE: The potential of using retinal images as a biomarker of cardiovascular disease (CVD) risk has gained significant attention, but regulatory approval of such artificial intelligence (AI) algorithms is lacking. In this regulated pivotal trial, we validated the efficacy of Reti-CVD, an AI-Software as a Medical Device (AI-SaMD), that utilizes retinal images to stratify CVD risk. MATERIALS AND METHODS: In this retrospective study, we used data from the Cardiovascular and Metabolic Diseases Etiology Research Center-High Risk (CMERC-HI) Cohort. Cox proportional hazard model was used to estimate hazard ratio (HR) trend across the 3-tier CVD risk groups (low-, moderate-, and high-risk) according to Reti-CVD in prediction of CVD events. The cardiac computed tomography-measured coronary artery calcium (CAC), carotid intima-media thickness (CIMT), and brachial-ankle pulse wave velocity (baPWV) were compared to Reti-CVD. RESULTS: A total of 1106 participants were included, with 33 (3.0%) participants experiencing CVD events over 5 years; the Reti-CVD-defined risk groups (low, moderate, and high) were significantly associated with increased CVD risk (HR trend, 2.02; 95% CI, 1.26-3.24). When all variables of Reti-CVD, CAC, CIMT, baPWV, and other traditional risk factors were incorporated into one Cox model, the Reti-CVD risk groups were only significantly associated with increased CVD risk (HR = 2.40 [0.82-7.03] in moderate risk and HR = 3.56 [1.34-9.51] in high risk using low-risk as a reference). DISCUSSION: This regulated pivotal study validated an AI-SaMD, retinal image-based, personalized CVD risk scoring system (Reti-CVD). CONCLUSION: These results led the Korean regulatory body to authorize Reti-CVD.