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AI predictive models and advancements in microdissection testicular sperm extraction for non-obstructive azoospermia: a systematic scoping review.
Hum Reprod Open
November 2024
Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Study Question: How accurately can artificial intelligence (AI) models predict sperm retrieval in non-obstructive azoospermia (NOA) patients undergoing micro-testicular sperm extraction (m-TESE) surgery?
Summary Answer: AI predictive models hold significant promise in predicting successful sperm retrieval in NOA patients undergoing m-TESE, although limitations regarding variability of study designs, small sample sizes, and a lack of validation studies restrict the overall generalizability of studies in this area.
What Is Known Already: Previous studies have explored various predictors of successful sperm retrieval in m-TESE, including clinical and hormonal factors. However, no consistent predictive model has yet been established.
Detection of neurologic changes in critically ill infants using deep learning on video data: a retrospective single center cohort study.
EClinicalMedicine
December 2024
Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Background: Infant alertness and neurologic changes can reflect life-threatening pathology but are assessed by physical exam, which can be intermittent and subjective. Reliable, continuous methods are needed. We hypothesized that our computer vision method to track movement, pose artificial intelligence (AI), could predict neurologic changes in the neonatal intensive care unit (NICU).
View Article and Find Full Text PDFA systematic review on the application of precision livestock farming technologies to detect lying, rest and sleep behavior in dairy calves.
Front Vet Sci
December 2024
Department of Veterinary Medicine and Animal Sciences, University of Milan, Lodi, Italy.
Welfare studies are increasingly involving the application of Precision Livestock Farming (PLF) sensors, rather than the use of animal-based indicators directly assessed. PLF technology has the advantage to constantly monitor behavior over a long period of time, thus enabling the assessor to identify changes in animal time budgets in real-time. In calves, lying behavior is essential: new-borns have been reported to spend 70-80% of their daily time lying.
View Article and Find Full Text PDFA systematic review and meta-analysis of health-related quality of life among patients with cardiovascular diseases in Ethiopia.
Front Cardiovasc Med
December 2024
Department of Reproductive Health, Teda Health Science College, Gondar, Ethiopia.
Introduction: Despite Ethiopia's best efforts, the physical, psychological, social, and environmental aspects of quality of life among patients with cardiovascular illnesses such as hypertension have not received adequate consideration. The quality of life among patients with cardiovascular diseases in Ethiopia has not been thoroughly examined; therefore, this study aimed to assess the prevalence and factors associated with health-related quality of life among patients with cardiovascular diseases.
Methods: The results of this systematic review and meta-analysis were reported in accordance with the International Recommended Reporting items for Systematic Review and Meta-analysis guidelines.
The transgenic SOD1G93A mouse model is the most widely used animal model of amyotrophic lateral sclerosis (ALS), a fatal disease of motor neuron degeneration. While genetic background influences onset and progression variability of motor dysfunction, the C57BL/6 background most reliably exhibits robust ALS phenotypes; thus, it is the most widely used strain in mechanistic studies. In this model, paresis begins in the hindlimbs and spreads rostrally to the forelimbs.
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