AIMC Topic: Male

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Accurate fall risk classification in elderly using one gait cycle data and machine learning.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Falls among the elderly are a major societal problem. While observations of medium-distance walking using inertial sensors identified potential fall predictors, classifying individuals at risk based on single gait cycles remains elusive. ...

Comparing and assessing four AI chatbots' competence in economics.

PloS one
Artificial Intelligence (AI) chatbots have emerged as powerful tools in modern academic endeavors, presenting both opportunities and challenges in the learning landscape. They can provide content information and analysis across most academic discipli...

Stacking with Recursive Feature Elimination-Isolation Forest for classification of diabetes mellitus.

PloS one
Diabetes Mellitus is one of the oldest diseases known to humankind, dating back to ancient Egypt. The disease is a chronic metabolic disorder that heavily burdens healthcare providers worldwide due to the steady increment of patients yearly. Worrying...

Child face detection on front passenger seat through deep learning.

Traffic injury prevention
OBJECTIVE: One of the main causes of death worldwide among young people are car crashes, and most of these fatalities occur to children who are seated in the front passenger seat and who, at the time of an accident, receive a direct impact from the a...

Frequently asked questions on erectile dysfunction: evaluating artificial intelligence answers with expert mentorship.

International journal of impotence research
The present study assessed the accuracy of artificiaI intelligence-generated responses to frequently asked questions on erectile dysfunction. A cross-sectional analysis involved 56 erectile dysfunction-related questions searched on Google, categorize...

Prediction of 6-Mo Poststroke Spasticity in Patients With Acute First-Ever Stroke by Machine Learning.

American journal of physical medicine & rehabilitation
OBJECTIVE: Poststroke spasticity reduces arm function and leads to low levels of independence. This study suggested applying machine learning from routinely available data to support the clinical management of poststroke spasticity.

Characterizing Osteophyte Formation in Knee Osteoarthritis: Application of Machine Learning Quantification of a Computerized Tomography Cohort: Implications for Treatment.

The Journal of arthroplasty
BACKGROUND: Osteophytes are commonly used to diagnose and guide knee osteoarthritis (OA) treatment, but their causes are unclear. Although they are not typically the focus of knee arthroplasty surgeons, they can predict case difficulty and length. Fu...

Artificial intelligence as a prediction tool for orthognathic surgery assessment.

Orthodontics & craniofacial research
INTRODUCTION: An ideal orthodontic treatment involves qualitative and quantitative measurements of dental and skeletal components to evaluate patients' discrepancies, such as facial, occlusal, and functional characteristics. Deciding between orthodon...

New perspectives in the differential diagnosis of jaw lesions: Machine learning and inflammatory biomarkers.

Journal of stomatology, oral and maxillofacial surgery
This study aimed to assess the diagnostic performance of a machine learning approach that utilized radiomic features extracted from Cone Beam Computer Tomography (CBCT) images and inflammatory biomarkers for distinguishing between Dentigerous Cysts (...

RSV Severe Infection Risk Stratification in a French 5-Year Birth Cohort Using Machine-learning.

The Pediatric infectious disease journal
BACKGROUND: Respiratory syncytial virus (RSV) poses a substantial threat to infants, often leading to challenges in hospital capacity. With recent pharmaceutical developments to be used during the prenatal and perinatal periods aimed at decreasing th...