State-of-art technologies, challenges, and emerging trends of computer vision in dental images.

Computer vision falls under the broad umbrella of artificial intelligence that mimics human vision and plays a vital role in dental imaging. Dental practitioners visualize and interpret teeth, and the structure surrounding the teeth and detect abnormalities by manually examining various dental imaging modalities. Due to the complexity and cognitive difficulty of comprehending medical data, human error makes correct diagnosis difficult. Automated diagnosis may be able to help alleviate delays, hasten practitioners' interpretation of positive cases, and lighten their workload. Several medical imaging modalities like X-rays, CT scans, color images, etc. that are employed in dentistry are briefly described in this survey. Dentists employ dental imaging as a diagnostic tool in several specialties, including orthodontics, endodontics, periodontics, etc. In the discipline of dentistry, computer vision has progressed from classic image processing to machine learning with mathematical approaches and robust deep learning techniques. Here conventional image processing techniques solely as well as in conjunction with intelligent machine learning algorithms, and sophisticated architectures of dental radiograph analysis employ deep learning techniques. This study provides a detailed summary of several tasks, including anatomical segmentation, identification, and categorization of different dental anomalies with their shortfalls as well as future perspectives in this field.

Morning light treatment for inflammatory bowel disease: a clinical trial.

BACKGROUND: Inflammatory bowel disease (IBD) affects over 3 million Americans and has a relapsing and remitting course with up to 30% of patients experiencing exacerbations each year despite the availability of immune targeted therapies. An urgent need exists to develop adjunctive treatment approaches to better manage IBD symptoms and disease activity. Circadian disruption is associated with increased disease activity and may be an important modifiable treatment target for IBD. Morning light treatment, which advances and stabilizes circadian timing, may have the potential to improve IBD symptoms and disease activity, but no studies have explored these potential therapeutic benefits in IBD. Therefore, in this study, we aim to test the effectiveness of morning light treatment for patients with IBD. METHODS: We will recruit sixty-eight individuals with biopsy-proven IBD and clinical symptoms and randomize them to 4-weeks of morning light treatment or 4-weeks of treatment as usual (TAU), with equivalent study contact. Patient-reported outcomes (IBD-related quality of life, mood, sleep), clinician-rated disease severity, and a biomarker of gastrointestinal inflammation (fecal calprotectin) will be assessed before and after treatment. Our primary objective will be to test the effect of morning light treatment versus TAU on IBD-related quality of life and our secondary objectives will be to test the effects on clinician-rated disease activity, depression, and sleep quality. We will also explore the effect of morning light treatment versus TAU on a biomarker of gastrointestinal inflammation (fecal calprotectin), and the potential moderating effects of steroid use, restless leg syndrome, and biological sex. DISCUSSION: Morning light treatment may be an acceptable, feasible, and effective adjunctive treatment for individuals with active IBD suffering from impaired health-related quality of life. TRIAL REGISTRATION: The study protocol was registered on ClinicalTrials.gov as NCT06094608 on October 23, 2023, before recruitment began on February 1, 2024.

DNA Sequencing Technologies and DNA Barcoding.

DNA barcodes are short, standardized DNA segments that geneticists can use to identify all living taxa. On the other hand, DNA barcoding identifies species by analyzing these specific regions against a DNA barcode reference library. In its initial years, DNA barcodes sequenced by Sanger's method were extensively used by taxonomists for the characterization and identification of species. But in recent years, DNA barcoding by next-generation sequencing (NGS) has found broader applications, such as quality control, biomonitoring of protected species, and biodiversity assessment. Technological advancements have also paved the way to metabarcoding, which has enabled massive parallel sequ.encing of complex bulk samples using high-throughput sequencing techniques. In future, DNA barcoding along with high-throughput techniques will show stupendous progress in taxonomic classification with reference to available sequence data.

Non-invasive Estimation of Pressure Drop Across Aortic Coarctations: Validation of 0D and 3D Computational Models with In Vivo Measurements.

Blood pressure gradient ( Δ P ) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of Δ P estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N = 17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. Δ P across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. The 0D simulations were extremely efficient ( ∼ 15 s computation time) compared to 3D simulations ( ∼ 30 h computation time on a cluster). However, the 0D Δ P estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as Δ P ≥ 20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.

Assessment of Medication Safety Incidents Associated with High-alert Medication Use in Intensive Care Setting: A Clinical Pharmacist Approach.

Background: High-alert medications (HAMs) potentiate heightened risk of causing patient harm ranging from 0.24 to 89.6 errors per 100 prescriptions. High-alert medications are crucially utilized in the intensive care settings (ICUs) due to their excellent potential in delivering therapeutic efficacy, yet these medications could cause severe harm if used inappropriately. Despite the cautious use of these medications, medication safety issues persist, which compromises patient safety. Methods: A prospective interventional study was conducted in ICUs for a period of 6 months. The HAMs were adopted from the Institute for Safe Medication Practices (ISMP) list of HAMs that were used. A suitably designed medication error assessment form was used to capture the necessary data, including demographics, medications, medication error, and the contributing factors. The National Coordinating Council for Medication Error Reporting and Prevention (NCCMERP) index was used to categorize the medication errors (MEs). The error rate was calculated using error rate formula. Continuous variables were expressed as mean ± standard deviation, whereas categorical variables were presented in frequencies and percentages. Results: A total of 165 patients were enrolled during the study period, with 98 (59.4%) being male and 67 (40.6%) female. The majority [54 (32.73%)] of the study participants belonged to the 61-70 age range. A total of 204 MEs were reported, of which [92 (41.5%)] errors were prescribing errors, followed by documentation errors [69 (33.82%)] and administration errors [43 (21.08%)]. The baseline medication error rate was noted to be 160.12/1,000 patient days. Potassium chloride, tramadol, propranolol, aspirin, insulin, and metoprolol were identified as the most common HAMs to cause errors. According to NCC MERP classification, 41.18% were categorized as category B, followed by category C (35.78%). An overall of 666 contributing factors (CFs) were identified for 204 errors. Stress (24.32%) was the most common factor that contributed to the MEs, followed by workload (21.47%). Conclusion: While great strides have been adopted in error prevention, yet the goal of making HAM errors "never" event has not been achieved. Thus, an active surveillance by a clinical pharmacist could support the healthcare team in promoting patient care. How to cite this article: Aradhya PJ, Ravi R, Subhash Chandra BJ, Ramesh M, Chalasani SH. Assessment of Medication Safety Incidents Associated with High-alert Medications Use in Intensive Care Setting: A Clinical Pharmacist Approach. Indian J Crit Care Med 2023;27(12):917-922.

Non-invasive estimation of pressure drop across aortic coarctations: validation of 0D and 3D computational models with in vivo measurements.

Purpose: Blood pressure gradient (ΔP) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of ΔP estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Methods: Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N=17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. ΔP across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. Results: The 0D simulations were extremely efficient (~15 secs computation time) compared to 3D simulations (~30 hrs computation time on a cluster). However, the 0D ΔP estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as ΔP≥20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Conclusion: Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.

Photocatalytic degradation of fluoroquinolone antibiotics using chitosan biopolymer functionalized copper oxide nanoparticles prepared by facile sonochemical method.

Photocatalytic degradation is an excellent method for removing pharmaceutical residues due to their simplicity, ecological benignity, high efficiency, and exceptional stability. Herein, we demonstrate the sonochemically synthesised chitosan biopolymer functionalized copper oxide nanoparticles as an efficient photocatalyst for the degradation of fluoroquinolone-based antibiotics. The X-ray diffraction Rietveld refinement revealed the formation of single-phase copper oxide (CuO) with a monoclinic structure. The presence of biopolymer functionalization was corroborated by Fourier Transform Infrared spectroscopy by observing the -NH2 and -OH functional groups. The high-resolution transmission electron microscopic images inferred that Chitosan functionalized copper oxide (C-CuO) particles are nano-sized with a smooth texture and aggregation-free particles. The strong absorbance and the broad photoluminescence emission in the ultraviolet-visible region confirm the suitability of CuO and C-CuO nanoparticles for photocatalytic applications. The catalytic activity was studied against fluoroquinolone-based antibiotics such as ciprofloxacin and norfloxacin under direct sunlight illumination. Interestingly, the C-CuO catalyst demonstrated 71.07 % (@140 min.) and 71.9 % (@60 min.) of degradation for ciprofloxacin and norfloxacin, respectively. The obtained photocatalytic activity of the prepared CuO and C-CuO catalysts was superior to the CuO particles prepared by the coprecipitation method (CC-CuO).

Helpful activities during the COVID-19 pandemic: Perceived benefits and actual association with psychiatric symptoms and psychological wellbeing.

BACKGROUND: Few studies have rigorously examined the effectiveness of commonly reported coping activities during the COVID-19 pandemic. This study was designed to assess perceived helpful activities during the pandemic and to investigate the extent to which these activities were associated with psychological outcomes. METHOD: Adults living in the US (N = 204), who were part of a longitudinal family study of depression responded to an online survey. They reported on their perceived helpful activities during the pandemic. General linear regression models (GLM) were used to evaluate the association between perceived helpful activities and current psychiatric symptoms, controlling for demographic factors, and pre-pandemic psychiatric history and symptoms. RESULTS: The top perceived helpful activity during COVID-19 was communicating with friends/family via telephone text or video (75.5 %). However, of the top five activities endorsed, cooking/baking was associated with the most clinical outcomes, including lower anxiety/depression and greater psychological wellbeing (all ps < 0.05). These relationships were most prominent among younger individuals < age 40 years, females, and those with recent psychiatric history, although they extended to younger males, and individuals at high or low depression risk. LIMITATIONS: Close ended items limited variability in coping activities reported. The study lacked data on substance use. The sample was racially and ethnically homogenous. CONCLUSIONS: These findings move beyond anecdotal evidence that cooking/baking as a coping activity yields protection against psychopathology. Its ready accessibility and ability to confer benefits across a range of individual characteristics, make it a useful adjunct in therapeutic interventions for people confined to their homes.

Effect of aging and thermocycling on flexural strength of PEEK as a provisional restoration for full mouth rehabilitation - An In vitro study.

Introduction: To compare the flexural strength of autopolymerizing poly methyl methacrylate resins (PMMA) resin, CAD/CAM milled PMMA and CAD/CAM milled poly ether ether ketone (PEEK) when used as provisional restorative materials for long span situations in full mouth rehabilitation after aging and thermocycling. Materials and Methods: Sixty samples (25 mm × 2 mm × 2 mm) were fabricated using autopolymerizing PMMA resin (GROUP I), CAD/CAM milled PMMA (GROUP II) and PEEK (GROUP III). The groups were subdivided into A and B and subjected to 7 days of aging and 500 cycles of thermocycling (subgroup A) and 14 days of aging and 1000 cycles of thermocycling (subgroup B), respectively, and flexural strength was evaluated using a three-point bend test. The data were analyzed with student t test and pair-wise comparison of mean values was done by ANOVA. Results: The flexural strength of PEEK subjected to 7 days of aging and 500 cycles of thermocycling (III (A) - 6628.70 MPa) was the highest among all groups followed by PEEK subjected to 14 days of aging and 1000 cycles of thermocycling (III (B) - 3760.50 MPa). Conclusion: The mean flexural strength of PEEK was statistically significant than the other two materials tested and hence can be recommended for use as a provisional restorative material for long span situations in full mouth rehabilitation. However, the mean flexural strength of PEEK reduced approximately by 44% when subjected to further aging.

Pre- and Post-Pandemic Religiosity and Mental Health Outcomes: A Prospective Study.

Relatively few studies have prospectively examined the effects of known protective factors, such as religion, on pandemic-related outcomes. The aim of this study was to evaluate the pre- and post-pandemic trajectories and psychological effects of religious beliefs and religious attendance. Male and female adults (N = 189) reported their beliefs in religious importance (RI) and their religious attendance (RA) both before (T1) and after (T2) the pandemic's onset. Descriptive and regression analyses were used to track RI and RA from T1 to T2 and to test their effects on psychological outcomes at T1 and T2. The participants who reported a decrease in religious importance and attendance were greater in number than those who reported an increase, with RI (36.5% vs. 5.3%) and RA (34.4% vs. 4.8%). The individuals with decreased RI were less likely to know someone who had died from COVID-19 (O.R. =0.4, p = 0.027). The T1 RI predicted overall social adjustment (p < 0.05) and lower suicidal ideation (p = 0.05). The T2 RI was associated with lower suicidal ideation (p < 0.05). The online RA (T2) was associated with lower depression (p < 0.05) and lower anxiety (p < 0.05). Further research is needed to evaluate the mechanisms driving decreases in religiosity during pandemics. Religious beliefs and online religious attendance were beneficial during the pandemic, which bodes well for the use of telemedicine in therapeutic approaches.

Association of maternal exposure to Superstorm Sandy and maternal cannabis use with development of psychopathology among offspring: the Stress in Pregnancy Study.

BACKGROUND: Early-life adverse experiences can elevate the magnitude of the risk of developmental psychopathology, but the potential synergistic effects of multiple factors have not been well studied. AIMS: To determine whether prenatal exposures to maternal stress (Superstorm Sandy) and maternal cannabis use synergistically alter the risk of developmental psychopathology. METHOD: The study included 163 children (53.4% girls), longitudinally tracked (ages 2-5 years) in relation to the effects of two early-life adverse exposures (Superstorm Sandy and maternal cannabis use). Offspring were grouped by exposure status (neither, only maternal cannabis use, only Superstorm Sandy or both). DSM-IV disorders for offspring were derived from structured clinical interviews; caregiver-reported ratings of family stress and social support were also assessed. RESULTS: A total of 40.5% had been exposed to Superstorm Sandy and 24.5% to maternal cannabis use. Offspring exposed to both (n = 13, 8.0%), relative to those exposed to neither, had a 31-fold increased risk of disruptive behavioural disorders (DBDs) and a seven-fold increased risk of anxiety disorders. The synergy index demonstrated that offspring with two exposures had synergistic elevation in risk of DBDs (synergy index, 2.06, P = 0.03) and anxiety disorders (synergy index, 2.60, P = 0.004), compared with the sum of single risks. Offspring with two exposures had the highest parenting stress and lowest social support. CONCLUSIONS: Our findings are consistent with the double-hit model suggesting that offspring with multiple early-life adverse exposures (Superstorm Sandy and maternal cannabis use) have synergistically increased risks of mental health problems. Given the increasing frequency of major natural disasters and cannabis use, especially among women under stress, these findings have significant public health implications.

The effects of the pandemic on mental health in persons with and without a psychiatric history.

BACKGROUND: Prospective studies are needed to assess the influence of pre-pandemic risk factors on mental health outcomes following the COVID-19 pandemic. From direct interviews prior to (T1), and then in the same individuals after the pandemic onset (T2), we assessed the influence of personal psychiatric history on changes in symptoms and wellbeing. METHODS: Two hundred and four (19-69 years/117 female) individuals from a multigenerational family study were followed clinically up to T1. Psychiatric symptom changes (T1-to-T2), their association with lifetime psychiatric history (no, only-past, and recent psychiatric history), and pandemic-specific worries were investigated. RESULTS: At T2 relative to T1, participants with recent psychopathology (in the last 2 years) had significantly fewer depressive (mean, M = 41.7 v. 47.6) and traumatic symptoms (M = 6.6 v. 8.1, p < 0.001), while those with no and only-past psychiatric history had decreased wellbeing (M = 22.6 v. 25.0, p < 0.01). Three pandemic-related worry factors were identified: Illness/death, Financial, and Social isolation. Individuals with recent psychiatric history had greater Illness/death and Financial worries than the no/only-past groups, but these worries were unrelated to depression at T2. Among individuals with no/only-past history, Illness/death worries predicted increased T2 depression [B = 0.6(0.3), p < 0.05]. CONCLUSIONS: As recent psychiatric history was not associated with increased depression or anxiety during the pandemic, new groups of previously unaffected persons might contribute to the increased pandemic-related depression and anxiety rates reported. These individuals likely represent incident cases that are first detected in primary care and other non-specialty clinical settings. Such settings may be useful for monitoring future illness among newly at-risk individuals.

The formaldehyde treated guar meal and prill fat, agro industrial by-products as dietary rumen protected protein and energy source: improves growth performance, feed conversion, nutrient utilization, microbial protein synthesis, blood metabolites and economic efficiency in growing dairy buffalo (Bubalus bubalis) calves.

The study investigated the effects of protein replacement with formaldehyde-treated guar meal (FTGM) and prill fat (PF) in the diet on performance of growing dairy buffalo calves. Thirty-two feedlots Surti breed dairy buffalo calves (age, 7.31 ± 0.34 months and body weight, 90.69 ± 6.19 kg) were assigned into four dietary treatments (n-8 calves/each): (1) control group, supplied basal diet as per ICAR (2013) nutrient requirements; (2) FTGM group, 30% crude protein (CP) requirement of concentrate mixture (dry matter basis (DMB)) replaced with FTGM in basal diet; (3) PF group, supplied basal diet + 100 g PF; and (4) FTGM + PF group, 30% CP requirement of concentrate mixture (DMB) replaced with FTGM in the basal diet + 100 g PF for 280 days. All the treatment diets were isonitrogenous. Growth performance was improved in FTGM + PF and FTGM groups. Apparent digestibility (%) of CP was increased in FTGM and FTGM + PF diet, while digestibility (%) of ether extract (EE) was increased in PF group. Serum total protein, albumen, urea nitrogen, and creatinine concentrations were higher in FTGM + PF and FTGM groups, whereas total cholesterol and triglycerides levels were greater in FTGM + PF and PF groups. Calculated methane emission had a discernible influence of treatment in FTGM and FTGM + PF. The overall cost of feeding per kilogram gain was lowest in FTGM and FTGM + PF groups. In conclusion, 30% CP replacement with FTGM with or without PF improved the growth performance, feed conversion ratio, and nutrient utilization; supported efficient utilization of resources; and economized the rearing of growing dairy buffalo calves.

Biomolecular docking interactions, cytotoxicity and antioxidant property evaluations with novel Mn(II), Ni(II), Cd(II) and Pb(II) Schiff base ligand complexes: Synthesis and characterization.

The development of Schiff base-centered medical chemistry in conjunction with the use of less-expensive transition metals with high pharmacological activity has currently triggered enormous interest in the development of novel Schiff base ligands. In this context, four different metal complexes comprising Mn(II), Ni(II), Cd(II) and Pb(II) (labeled as complexes 1-4) were synthesized using a novel tetra-dentate ligand (L) obtained by condensation of 3,5-dichlorosalicylaldehyde and trans-1,2-diaminocyclohexane, as demonstrated herein. The physico-chemical properties of the complexes were evaluated through UV-Vis, FT-IR, NMR, TGA, powder XRD and ESI-MS analyses. The crystalline states of the metal complexes were analysed by powder XRD. The existence of the lattice as well as coordinated water molecules in the complexes were demonstrated by the thermal characteristics of the complexes. The thermal stability of all the compounds is due to their high melting points. Studies on the free radical scavenging and antibacterial properties performed with the ligand L and the synthesized metal complexes 1-4 revealed that the Ni(II) complex had higher efficiency. Also, their bactericidal properties were tested with gram-positive (Staphylococcus aureus) and gram-negative (Escherichia coli) bacteria. Using Ni(II) as a model, anticancer studies for MCF-7 breast cancer cell lines were performed. By using molecular docking studies, the interactions between drugs and biomolecules were identified. The Ni(II) complex showed synergistic activity, exemplifying its stronger anticancer action, establishing its higher inhibiting efficiency of 68.26% at 320 g/mL. The present investigation, therefore, acknowledges the viability of these newly synthesized Schiff base-derived complexes as clinical-trial prodrugs.

Social connectedness as a determinant of mental health: A scoping review.

Public health and epidemiologic research have established that social connectedness promotes overall health. Yet there have been no recent reviews of findings from research examining social connectedness as a determinant of mental health. The goal of this review was to evaluate recent longitudinal research probing the effects of social connectedness on depression and anxiety symptoms and diagnoses in the general population. A scoping review was performed of PubMed and PsychInfo databases from January 2015 to December 2021 following PRISMA-ScR guidelines using a defined search strategy. The search yielded 66 unique studies. In research with other than pregnant women, 83% (19 of 23) studies reported that social support benefited symptoms of depression with the remaining 17% (5 of 23) reporting minimal or no evidence that lower levels of social support predict depression at follow-up. In research with pregnant women, 83% (24 of 29 studies) found that low social support increased postpartum depressive symptoms. Among 8 of 9 studies that focused on loneliness, feeling lonely at baseline was related to adverse outcomes at follow-up including higher risks of major depressive disorder, depressive symptom severity, generalized anxiety disorder, and lower levels of physical activity. In 5 of 8 reports, smaller social network size predicted depressive symptoms or disorder at follow-up. In summary, most recent relevant longitudinal studies have demonstrated that social connectedness protects adults in the general population from depressive symptoms and disorders. The results, which were largely consistent across settings, exposure measures, and populations, support efforts to improve clinical detection of high-risk patients, including adults with low social support and elevated loneliness.

Putamen Structure and Function in Familial Risk for Depression: A Multimodal Imaging Study.

BACKGROUND: The putamen has been implicated in depressive disorders, but how its structure and function increase depression risk is not clearly understood. Here, we examined how putamen volume, neuronal density, and mood-modulated functional activity relate to family history and prospective course of depression. METHODS: The study includes 115 second- and third-generation offspring at high or low risk for depression based on the presence or absence of major depressive disorder in the first generation. Offspring were followed longitudinally using semistructured clinical interviews blinded to their familial risk; putamen structure, neuronal integrity, and functional activation were indexed by structural magnetic resonance imaging (MRI), proton magnetic resonance spectroscopy (N-acetylaspartate/creatine ratio), and functional MRI activity modulated by valence and arousal components of a mood induction task, respectively. RESULTS: After adjusting for covariates, the high-risk individuals had lower putamen volume (standardized betas, ß-left = -0.17, ß-right = -0.15, ps = .002), N-acetylaspartate/creatine ratio (ß-left= -0.40, ß-right= -0.37, ps < .0001), and activation modulated by valence (ß-left = -0.22, ß-right = -0.27, ps < .05) than low-risk individuals. Volume differences were greater at younger ages, and N-acetylaspartate/creatine ratio differences were greater at older ages. Lower putamen volume also predicted major depressive disorder episodes up to 8 years after the scan (ß-left = -0.72, p = .013; ß-right = -0.83, p = .037). Magnetic resonance spectroscopy and task functional MRI measures were modestly correlated (0.27 ≤ r ≤ 0.33). CONCLUSIONS: Findings demonstrate abnormalities in putamen structure and function in individuals at high risk for major depressive disorder. Future studies should focus on this region as a potential biomarker for depressive illness, noting meanwhile that differences attributable to family history may peak at different ages based on which MRI modality is being used to assay them.

Towards applying internet of things and machine learning for the risk prediction of COVID-19 in pandemic situation using Naive Bayes classifier for improving accuracy.

Infections such as COVID-19 are affecting the entire world and measures such as social distancing can be done so that the contact among people is reduced. IoT devices usage keeps on increasing every day thereby connecting the environments physically. Among the current technologies, machine learning can be employed along with IoT devices. Predicting the risk related with COVID-19, a novel method employing machine learning is proposed. Random forest and Naive Bayes classifier are used for the prediction from the data collected with the help of sensors. Groups of people are recognized and the disease impact can be reduced for the particular group with more population. The accuracy of RF is 97% and for NB it is 99%.