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A 3D multi-task network for the automatic segmentation of CT images featuring hip osteoarthritis.

Biomedical physics & engineering express
Total hip arthroplasty (THA) is the primary treatment for end-stage hip osteoarthritis, with successful outcomes depending on precise preoperative planning that requires accurate segmentation and reconstruction of periarticular bone of the hip joint....

MRI detection and grading of knee osteoarthritis - a pilot study using an AI technique with a novel imaging-based scoring system.

Biomaterials science
Precise and rapid identification of knee osteoarthritis (OA) is essential for efficient management and therapy planning. Conventional diagnostic techniques frequently depend on subjective interpretation, which have shortcomings, particularly during t...

Mapping the impact: AI-driven quantification of geographic atrophy on OCT scans and its association with visual sensitivity loss.

The British journal of ophthalmology
BACKGROUND/AIMS: To examine the association between artificial intelligence (AI)-driven segmentation of geographic atrophy (GA) on optical coherence tomography (OCT) and visual sensitivity loss quantified by defect-mapping microperimetry, a testing s...

SpinalTRAQ: A Novel Pipeline for Volumetric Cervical Spinal Cord Analysis Identifies the Corticospinal Tract Synaptic Projectome in Healthy and Post-stroke Mice.

eNeuro
The corticospinal tract (CST) is essential for forelimb-specific fine motor skills. In rodents, it undergoes extensive structural remodeling across development, injury, and disease states, with major implications for motor function. A vast body of li...

Linking dynamic connectivity states to cognitive decline and anatomical changes in Alzheimer's disease.

NeuroImage
Alterations in brain connectivity provide early indications of neurodegenerative diseases like Alzheimer's disease (AD). Here, we present a novel framework that integrates a Hidden Markov Model (HMM) within the architecture of a convolutional neural ...

Predictors of Anemia Intolerance for Real-Time Transfusion Decision-Making During Resuscitation of Trauma Subjects: A Machine Learning Approach Using Heart Rate Variability.

Critical care explorations
OBJECTIVES: RBC transfusion in anemic patients with sustainable tolerance may cause harm, emphasizing the need for reliable metrics that quantify adequacy (oxygen delivery ≥ demand) and sustainability (oxygen delivery remains adequate without transfu...

Artificial intelligence in the prescription of acute medical treatments in primary healthcare - comparison of the performance of family physicians and ChatGPT.

BMC primary care
INTRODUCTION: Artificial intelligence (AI) is increasingly being recognized as a transformative force in healthcare, showing significant promise in supporting healthcare professionals. AI has many applications in healthcare, including providing real-...

Using Machine Learning Methods to Predict Early Treatment Outcomes for Multidrug-Resistant or Rifampicin-Resistant Tuberculosis to Enhance Patient Cure Rates: Development and Validation of Multiple Models.

Journal of medical Internet research
BACKGROUND: Early prediction of treatment outcomes for patients with multidrug-resistant or rifampicin-resistant tuberculosis (MDR/RR-TB) undergoing extended therapy is crucial for enhancing clinical prognoses and preventing the transmission of this ...