Machine Learning Driven by Magnetic Resonance Imaging for the Classification of Alzheimer Disease Progression: Systematic Review and Meta-Analysis.

Background: To diagnose Alzheimer disease (AD), individuals are classified according to the severity of their cognitive impairment. There are currently no specific causes or conditions for this disease.

Objective: The purpose of this systematic review and meta-analysis was to assess AD prevalence across different stages using machine learning (ML) approaches comprehensively.

Complications after low-velocity ballistic femur fractures: a series of 104 patients at a level 1 trauma center.

Objectives: To report outcomes and risk factors of complications following low-velocity ballistic fractures of the femur.

Design: Retrospective case series.

Setting: Academic Level I trauma center.

Deep infections after low-velocity ballistic tibia fractures are frequently polymicrobial and recalcitrant.

Objectives: To identify risk factors for developing a fracture-related infection in operatively treated ballistic tibia fractures and to report the microbiologic results of intraoperative cultures.

Design: Retrospective review.

Setting: Level 1 trauma center.

Approaches to Medical Emergencies on Commercial Flights.

In-flight medical incidents are becoming increasingly critical as passengers with diverse health profiles increase in the skies. In this paper, we reviewed how airlines, aviation authorities, and healthcare professionals respond to such emergencies. The analysis was focused on the strategies developed by the top ten airlines in the world by examining training in basic first aid, collaboration with ground-based medical support, and use of onboard medical equipment.

Brain Tumor Detection and Categorization with Segmentation of Improved Unsupervised Clustering Approach and Machine Learning Classifier.

There is no doubt that brain tumors are one of the leading causes of death in the world. A biopsy is considered the most important procedure in cancer diagnosis, but it comes with drawbacks, including low sensitivity, risks during biopsy treatment, and a lengthy wait for results. Early identification provides patients with a better prognosis and reduces treatment costs.