Artificial Intelligence (AI) has emerged as a transformative technology with immense potential in the field of medicine. By leveraging machine learning and deep learning, AI can assist in diagnosis, treatment selection, and patient monitoring, enabling more accurate and efficient healthcare delivery. The widespread implementation of AI in healthcare has the role to revolutionize patients’ outcomes and transform the way healthcare is practiced, leading to improved accessibility, affordability, and quality of care. This article explores the diverse applications and reviews the current state of AI adoption in healthcare. It concludes by emphasizing the need for collaboration between physicians and technology experts to harness the full potential of AI.

This review provides a comprehensive analysis of the transformative role of artificial intelligence (AI) in predicting and preventing sports injuries across various disciplines. By exploring the application of machine learning (ML) and deep learning (DL) techniques, such as random forests (RFs), convolutional neural networks (CNNs), and artificial neural networks (ANNs), this review highlights AI’s ability to analyze complex datasets, detect patterns, and generate predictive insights that enhance injury prevention strategies. AI models improve the accuracy and reliability of injury risk assessments by tailoring prevention strategies to individual athlete profiles and processing real-time data. A literature review was conducted through searches in PubMed, Google Scholar, Science Direct, and Web of Science, focusing on studies from 2014 to 2024 and using keywords such as ‘artificial intelligence’, ‘machine learning’, ‘sports injury’, and ‘risk prediction’. While AI’s predictive power supports both team and individual sports, its effectiveness varies based on the unique data requirements and injury risks of each, with team sports presenting additional complexity in data integration and injury tracking across multiple players. This review also addresses critical issues such as data quality, ethical concerns, privacy, and the need for transparency in AI applications. By shifting the focus from reactive to proactive injury management, AI technologies contribute to enhanced athlete safety, optimized performance, and reduced human error in medical decisions. As AI continues to evolve, its potential to revolutionize sports injury prediction and prevention promises further advancements in athlete health and performance while addressing current challenges.

Background: The integration of artificial intelligence (AI) into various fields has ushered in a new era of multidisciplinary progress. Defined as the ability of a system to interpret external data, learn from it, and adapt to specific tasks, AI is poised to revolutionize the world. In forensic medicine and pathology, algorithms play a crucial role in data analysis, pattern recognition, anomaly identification, and decision making. This review explores the diverse applications of AI in forensic medicine, encompassing fields such as forensic identification, ballistics, traumatic injuries, postmortem interval estimation, forensic toxicology, and more. Results: A thorough review of 113 articles revealed a subset of 32 papers directly relevant to the research, covering a wide range of applications. These included forensic identification, ballistics and additional factors of shooting, traumatic injuries, post-mortem interval estimation, forensic toxicology, sexual assaults/rape, crime scene reconstruction, virtual autopsy, and medical act quality evaluation. The studies demonstrated the feasibility and advantages of employing AI technology in various facets of forensic medicine and pathology. Conclusions: The integration of AI in forensic medicine and pathology offers promising prospects for improving accuracy and efficiency in medico-legal practices. From forensic identification to post-mortem interval estimation, AI algorithms have shown the potential to reduce human subjectivity, mitigate errors, and provide cost-effective solutions. While challenges surrounding ethical considerations, data security, and algorithmic correctness persist, continued research and technological advancements hold the key to realizing the full potential of AI in forensic applications. As the field of AI continues to evolve, it is poised to play an increasingly pivotal role in the future of forensic medicine and pathology.

Sleep disturbances are common in various neurological pathologies, including amyotrophic lateral sclerosis (ALS), multiple system atrophy (MSA), hereditary ataxias, Huntington’s disease (HD), progressive supranuclear palsy (PSP), and dementia with Lewy bodies (DLB). This article reviews the prevalence and characteristics of sleep disorders in these conditions, highlighting their impact on patients’ quality of life and disease progression. Sleep-related breathing disorders, insomnia, restless legs syndrome (RLS), periodic limb movement syndrome (PLMS), and rapid eye movement sleep behavior disorder (RBD) are among the common sleep disturbances reported. Both pharmacological and non-pharmacological interventions play crucial roles in managing sleep disturbances and enhancing overall patient care.

Background (1): Men’s football is a physically demanding contact sport that involves intermittent bouts of sprinting, jogging, walking, jumping and changes of direction. The physical demands of the game vary by level of play (amateur club, sub-elite and open club or international), but injury rates at all levels of the men’s football game remain the highest of all sports. Objective: The aim of this study is to conduct a systematic review of data from the epidemiological literature regarding the profile, severity and mechanisms of injuries and the frequency of recurrent injuries in professional and amateur football players. Methods (2): A systematic review, according to PRISMA guidelines, was performed up to June 2023 in the databases of PubMed, Web of Science, Google academic, Google scholar and the Diva portal. Twenty-seven studies that reported data on the type, severity, recurrence and mechanisms of injury in professional and amateur men’s football were selected and analyzed. Two reviewers independently audited data and assessed the study quality using the additional and adapted version of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and the Newcastle Ottawa Scale (NOS) to assess risk of bias for the quality of external validity. Results (3): In professional male football players, the mean prevalence of muscle/tendon injuries was 39.78%, followed by joint and ligament injuries—21.13%, contusions—17.86%, and fractures—3.27%, and for amateur football players, the prevalence’s were 44.56% (muscle/tendon injuries), 27.62% (joint and ligament injuries), 15.0% (contusions) and 3.05% (fracture), respectively. The frequency of traumatic injuries was higher in amateur football players (76.88%) compared to professional football players (64.16%), the situation being reversed in the case of overuse injuries: 27.62% in professional football players and 21.13% in amateur football players. Most contact injuries were found in professional footballers (50.70%), with non-contact injuries predominating in amateur footballers (54.04%). The analysis of the severity of injuries showed that moderate injuries dominated in the two categories of footballers; the severe injuries in amateur footballers exceeded the severe injuries recorded in professional footballers by 9.60%. Recurrence proportions showed an inverse relationship with the level of play, being higher in amateur footballers (16.66%) compared to professional footballers (15.25%). Conclusions (4): Football-related injuries have a significant impact on professional and amateur football players and their short- and long-term health status. Knowing the frequency of severe diagnoses, such as strains, tears and cramps of the thigh muscles, ankle ligament sprains and hip/groin muscle strain requires the establishment of adequate programs to prevent them, especially in amateur football players, who are more prone to serious injuries.

Background (1): Football is the most popular sport among men, associated with a certain risk of injury, which leads to short- and long-term health consequences. While the injury profile of professional footballers is known, little is known about the injury profile of amateur footballers; amateur football is a major and diverse area, the development of which should be a priority for football associations around the world and UEFA. The aim of this study was to perform a systematic review of epidemiological literature data on injuries in professional and amateur football players belonging to certain leagues. Methods (2): A systematic review according to the PRISMA guidelines was performed until June 2023 in the databases PubMed, Web of Science, Google Academic, Google Scholar, and Diva portal. Forty-six studies reporting injury incidence in professional and amateur men’s football were selected and analyzed. Two reviewers independently extracted data and assessed study quality using an adapted version of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and the Newcastle Ottawa Scale (NOS) to assess risk of bias for the quality of external validity. Results (3): The overall incidence of injuries in professional male football players was 7.75 ± 2.28, 95% confidence interval, injuries/1000 h of exposure and that of amateur football players was 7.98 ± 2.95, 95% confidence interval, injuries/1000 h of exposure. The incidence of match injuries (30.64 ± 10.28, 95% confidence interval, injuries/1000 exposure hours) was 7.71 times higher than the training injury incidence rate (3.97 ± 1.35, 95% confidence interval, injuries/1000 h) in professional football players and 5.45 times higher in amateurs (17.56 ± 6.15 vs. 3.22 ± 1.4, 95% confidence interval, injuries/1000 h). Aggregate lower extremity injuries had the highest prevalence in both categories of footballers, being 83.32 ± 4.85% in professional footballers and 80.4 ± 7.04% in amateur footballers: thigh, ankle, and knee injuries predominated. Conclusions (4): Professional and amateur football players are at substantial risk of injury, especially during matches that require the highest level of performance. Injury rates have implications for players, coaches, and sports medicine practitioners. Therefore, information on football injuries can help develop personalized injury risk mitigation strategies that could make football safer for both categories of football players. The current findings have implications for the management, monitoring, and design of training, competition, injury prevention, especially severe injury, and education programs for amateur football players.