Combined Quantitative amyloid-β PET and Structural MRI Features Improve Alzheimer's Disease Classification in Random Forest Model - A Multicenter Study.

Rationale And Objectives: Prior to clinical presentations of Alzheimer's Disease (AD), neuropathological changes, such as amyloid-β and brain atrophy, have accumulated at the earlier stages of the disease. The combination of such biomarkers assessed by multiple modalities commonly improves the likelihood of AD etiology. We aimed to explore the discriminative ability of Aβ PET features and whether combining Aβ PET and structural MRI features can improve the classification performance of the machine learning model in older healthy control (OHC) and mild cognitive impairment (MCI) from AD.

Performance of GPT-4 and GPT-3.5 in generating accurate and comprehensive diagnoses across medical subspecialties.

Artificial intelligence has demonstrated a promising potential for diagnosing complex medical cases, with Generative Pre-Trained Transformer 4 (GPT-4) being the most recent advancement in this field. This study evaluated the diagnostic performance of the GPT-4 in comparison with that of its predecessor, GPT-3.5, using 81 complex medical case records from the New England Journal of Medicine .

The Effect of Social Isolation on 1-Year Outcomes After Surgical Repair of Low-Energy Hip Fracture.

Objectives: To evaluate whether social isolation or loneliness is associated with outcomes 1 year after low-energy hip fracture.

Design: Prospective inception cohort study.

Setting: Academic level I trauma center.

Limitations of GPT-4 as a geriatrician in geri-oncology case conference: A case series.

Generative pre-trained transformer 4 (GPT-4) is an artificial intelligence (AI) system with a chat interface. The number of studies testing GPT-4 in clinical applications has been increasing. We hypothesized that GPT-4 would be able to suggest management strategies for medical issues in elderly oncology patients, similar to those provided by geriatricians.