AIMC Topic: Male

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Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.

Pediatrics
OBJECTIVES: Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluate the effectiveness of artificial intelligence (AI)-based screening in an Indian ROP telemedicine pr...

Enhancing Military Burn- and Trauma-Related Acute Kidney Injury Prediction Through an Automated Machine Learning Platform and Point-of-Care Testing.

Archives of pathology & laboratory medicine
CONTEXT.—: Delayed recognition of acute kidney injury (AKI) results in poor outcomes in military and civilian burn-trauma care. Poor predictive ability of urine output (UOP) and creatinine contribute to the delayed recognition of AKI.

Artificial Intelligence Algorithm for Screening Heart Failure with Reduced Ejection Fraction Using Electrocardiography.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
Although heart failure with reduced ejection fraction (HFrEF) is a common clinical syndrome and can be modified by the administration of appropriate medical therapy, there is no adequate tool available to perform reliable, economical, early-stage scr...

Use of Telepresence Robots in Glaucoma Patient Education.

Journal of glaucoma
PRCIS: Telepresence robots (TR) present the versatility to effectively provide remote educational sessions for patients affected by glaucoma to improve disease knowledge. Given COVID-19's effect on clinical practice, TR can maintain social distancing...

Robotic-assisted locomotor treadmill therapy does not change gait pattern in children with cerebral palsy.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation
Although robotic-assisted locomotor treadmill therapy is utilized on children with cerebral palsy (CP), its impact on the gait pattern in childhood is not fully described. We investigated the outcome of robotized gait training focusing on the gait pa...

Predicting 2-Day Mortality of Thrombocytopenic Patients Based on Clinical Laboratory Data Using Machine Learning.

Medical care
BACKGROUND: Clinical laboratories have traditionally used a single critical value for thrombocytopenic events. This system, however, could lead to inaccuracies and inefficiencies, causing alarm fatigue and compromised patient safety.

Classifying Pseudogout Using Machine Learning Approaches With Electronic Health Record Data.

Arthritis care & research
OBJECTIVE: Identifying pseudogout in large data sets is difficult due to its episodic nature and a lack of billing codes specific to this acute subtype of calcium pyrophosphate (CPP) deposition disease. The objective of this study was to evaluate a n...

[Application of deep learning-based chest CT auxiliary diagnosis system in emergency trauma patients].

Zhonghua yi xue za zhi
To investigate the diagnostic efficacy and potential application value of deep learning-based chest CT auxiliary diagnosis system in emergency trauma patients. A total of 403 patients, including 254 males and 149 females aged from 16 to 100 (50±19)...

Identifying key predictors of mortality in young patients on chronic haemodialysis-a machine learning approach.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
BACKGROUND: The mortality risk remains significant in paediatric and adult patients on chronic haemodialysis (HD) treatment. We aimed to identify factors associated with mortality in patients who started HD as children and continued HD as adults.