The effect of machine learning algorithms in the prediction, and diagnosis of meningitis: A systematic review.

Background and Aims: This systematic review aimed to evaluating the effectiveness of machine learning (ML) algorithms for the prediction and diagnosis of meningitis. Methods: On November 12, 2022, a systematic review was carried out using a keyword search in the reliable scientific databases PubMed, EMBASE, Scopus, and Web of Science. The recommendations of Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) were adhered to. Studies conducted in English that employed ML to predict and identify meningitis were deemed to match the inclusion criteria. The eligibility requirements were used to independently review the titles and abstracts. The whole text was then obtained and independently reviewed in accordance with the eligibility requirements. Results: After all the research matched the inclusion criteria, a total of 16 studies were added to the systematic review. Studies on the application of ML algorithms in the three categories of disease diagnosis ability (8.16) and disease prediction ability (8.16) (including cases related to identifying patients (50%), risk of death in patients (25%), the consequences of the disease in childhood (12.5%), and its etiology [12.5%]) were placed. Among the ML algorithms used in this study, logistic regression (LR) (4.16, 25%) and multiple logistic regression (MLR) (4.16, 25%) were the most used. All the included studies indicated improvements in the processes of diagnosis, prediction, and disease outbreak with the help of ML algorithms. Conclusion: The results of the study showed that in all included studies, ML algorithms were an effective approach to facilitate diagnosis, predict consequences for risk classification, and improve resource utilization by predicting the volume of patients or services as well as discovering risk factors. The role of ML algorithms in improving disease diagnosis was more significant than disease prediction and prevalence. Meanwhile, the use of combined methods can optimize differential diagnoses and facilitate the decision-making process for healthcare providers.

Use of Digital Games for Educational Purposes Among Medical and Paramedical Sciences Students, Mashhad, Iran.

This study aimed to investigate the use of digital games for educational purposes among medical and paramedical sciences students at Mashhad University of Medical Sciences (Northeast of Iran). This cross-sectional study was conducted from July 2018 to January 2019. The research population was all students of the school of medicine and school of paramedical sciences at Mashhad University of Medical Sciences (n = 496). The research tool was a researcher-made questionnaire based on a literature review. The validity of the questionnaire was confirmed by its content validity, and the reliability of the questionnaire was evaluated based on the test-retest method (r = 0.82). In this examination of medical and paramedical sciences students' attitudes and perspectives, some novel preliminary insights into the applications, advantages, disadvantages, and features of digital games in education emerge. Overall, the findings showed that the use of interactive digital games can increase students' motivation for learning and make the learning process more attractive for students. This study was approved by the ethical committee of MUMS (approval number IR.MUMS.REC.1397.151).

Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review.

Background and Aims: This systematic review examined healthcare students' attitudes, knowledge, and skill in Artificial Intelligence (AI). Methods: On August 3, 2022, studies were retrieved from the PubMed, Embase, Scopus, and Web of Science databases. Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations were followed. We included cross-sectional studies that examined healthcare students' knowledge, attitudes, skills, and perceptions of AI in this review. Using the eligibility requirements as a guide, titles and abstracts were screened. Complete texts were then retrieved and independently reviewed per the eligibility requirements. To collect data, a standardized form was used. Results: Of the 38 included studies, 29 (76%) of healthcare students had a positive and promising attitude towards AI in the clinical profession and its use in he future; however, in nine of the studies (24%), students considered AI a threat to healthcare fields and had a negative attitude towards it. Furthermore, 26 studies evaluated the knowledge of healthcare students about AI. Among these, 18 studies evaluated the level of student knowledge as low (50%). On the other hand, in six of the studies, students' high knowledge of AI was reported, and two of the studies reported average student general knowledge (almost 50%). Of the six studies, four (67%) of the students had very low skills, so they stated that they had never worked with AI. Conclusion: Evidence from this review shows that healthcare students had a positive and promising attitude towards AI in medicine; however, most students had low knowledge and limited skills in working with AI. Face-to-face instruction, training manuals, and detailed instructions are therefore crucial for implementing and comprehending how AI technology works and raising students' knowledge of the advantages of AI.

The trend of normal vaginal delivery and cesarean sections before and after implementing the health system transformation plan based on ICD-10 in the northeast of Iran: A cross-sectional study.

Background and Aims: Concerning the growing rate of cesarean sections (CSs) worldwide, encouraging normal vaginal deliveries (NVDs) and mitigating CS rates is a necessity. This study investigated the status of delivery in hospitals affiliated with the Mashhad University of Medical Sciences (MUMS) before and after implementing health system transformation plan (HSTP). Methods: A cross-sectional study was conducted in 2017 in the obstetrics and gynecology ward in four MUMS teaching hospitals. Data were extracted from hospital information systems (HISs) based on the International Classification of Diseases (ICD-10) and analyzed in SPSS VE10 software. Results: The results revealed a significant difference between the rate of NVDs and CSs before and after HSTP, such that implementing this plan in MUMS hospitals has raised the rate of NVDs by 4%. Except for the age groups of less than 15 and 36-40 years, the difference between NVD and CS was significant in different age groups before and after HSTP. The rate of NVD significantly increased within 2 months after implementing HSTP. Furthermore, the difference in the rate of previous CS before and after implementing HSTP was significant (p < 0.001). Conclusion: The results of this study show the positive impact of the implementation of the HSTP on CS reduction and NVD increase in the studied hospitals. Since the studied hospitals were teaching and concerning the different costs of NVD and CS between the public and private hospitals, it is recommended to study all hospitals with the obstetrics and gynecology ward to precisely assess the success of HSTP in encouraging NVD.

Attitude, awareness, and knowledge of telemedicine among medical students: A systematic review of cross-sectional studies.

Background and Aims: The success of every new technology depends on numerous factors, including specialists' knowledge and perceptions of the concept, acquired attitude skills, and work environments. This systematic review aimed to examine medical students' knowledge, attitudes, and perceptions of telemedicine. Methods: Studies were obtained from the PubMed, Embase, Scopus, and Web of Science databases on June 9, 2022. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Cross-sectional studies that examined medical students' knowledge, attitude, and perceptions of telemedicine approaches were considered inclusion criteria. Titles and abstracts were independently screened based on eligibility criteria. Articles that did not meet the inclusion criteria were excluded from this review. After that, the complete texts were retrieved and screened by two separate researchers based on the eligibility criteria. Disputes were resolved by discussion. The same checklist was used for data extraction. To assess the quality of the studies entering this study, the Joanna Briggs Institute Critical Appraisal Checklist for analytical cross-sectional studies was used. Results: In total, 10 eligible articles were found through this review. The sample size of the studies ranged from 60 to 3312 participants, or 6172 participants on the whole. The medical students' attitudes toward telemedicine were evaluated in eight included studies. Many of these studies (seven cases) reported positive and promising perspectives on telemedicine. However, in one study, participants revealed moderate attitudes toward online health information and online health experience sharing (p < 0.05). Students' knowledge of the telemedicine approach was evaluated in eight included studies. Many of these studies (five cases) reported that students possessed an extensively poor knowledge of telemedicine's uses. In three other studies, two reported moderate and one disclosed desirable levels of students' knowledge. All the included studies attributed medical students' poor knowledge to the lack of, and thus failure of, educational courses in this field. Conclusion: The evidence obtained from this review reveals that medical students possess positive and promising attitudes toward telemedicine technology for education, treatment, and care. However, their knowledge levels were extremely insufficient, and many had not passed any educational courses in this respect. Such results can foreground the health and education policymakers' obligations for planning, training, and empowering digital health and telemedicine literacy among medical students as the primary players in social health.

Occupational exposure to blood and body fluids among prehospital emergency medical services workers in Mashhad, Northeast of Iran.

BACKGROUND: This study aimed to assess occupational exposure to blood and body fluids (BBFs) and the use of protective equipment among prehospital emergency medical services (EMS) workers in Mashhad, Iran. METHODS: This cross-sectional questionnaire survey-based study was conducted from July 2020 to March 2021 in Mashhad. All prehospital EMS workers of Mashhad were invited to participate in the study using the census technique. The questionnaire was about occupational exposure to BBFs, infection control, protective measures, health program, and demographic information. RESULTS: In total, 442 participants answered the questionnaire (response rate: 82.77%). Based on the findings, 420 (95.2%) and 402 (91.2%) participants had been exposed to BBFs as prehospital EMS workers. Moreover, 31.5% and 38.5% of these exposures were caused by contaminated needles and lancets, respectively. The BBFs incidents have occurred despite 98% of the EMS workers reporting there is a needle safety disposable box in the ambulance. The relationship between awareness of precaution measures after exposure to BBFs and training course completion was significant (P < .0001). CONCLUSION: This study demonstrated the high prevalence of occupational exposures to BBFs among prehospital EMS workers. Considering the significant relationship between the completion of standard precautions courses and awareness of BBFs' postexposure measures, it is recommended to consider multi-faceted strategies for continuous monitoring, training, and follow-up of prehospital EMS workers.

Evaluating the Impact of Digital Game on Learning Medical Terminology of Paramedical Students: Protocol for a Randomized Controlled Trial.

This is a study protocol to evaluate the Impact of digital games on learning medical terminology of paramedical students. An unblinded randomized controlled trial (RCT) 2-arm, with 1:1 allocation ratio was randomized by 60 students at the faculty of paramedical science at Mashhad University of Medical Science(MUMS), Iran, who had their medical terminology course at the time of this study, would enter the study. To evaluate the game, Participants in both groups attended typical teaching in traditional instructional activities for two months; however, the intervention group played the smartphone-based digital game during the course. The knowledge level of students in the control and intervention group were measured before and immediately after the intervention using the pre-designed questionnaire. This study was approved by the ethical committee of MUMS (approval number IR.MUMS.REC.1400.336).

Type and Number of Errors of the Iranian Electronic Health Record (SEPAS) in Hospitals Affiliated with Mashhad University of Medical Sciences.

This study aims to identify the type and number of errors in the Iranian Electronic Health Record System (SEPAS) in hospitals affiliated with Mashhad University of Medical Sciences (MUMS). A cross-sectional analytical study was conducted to specify the errors done by SEPAS in the first half of 2019, based on the type and number of errors in 26 hospitals affiliated with MUMS that were connected to the SEPAS system. SEPAS system errors were classified into four categories: identity errors, clinical errors, administrative-financial and technical errors. The most important errors that occurred in the SEPAS system included non-authentication errors in Hospital Information System (HIS), non-service records, and invalid national code, respectively. Therefore, hospital administrators and information system developers must make an effort to prevent such errors.