Biases in the performance of FRAX without BMD in predicting fracture risk in a multiethnic population with diabetes: the Diabetes & Aging Study.

Fracture risk calculators, such as the Fracture Risk Assessment Tool (FRAX), calculate the risk of major osteoporotic (MOF) and hip fracture, but do not account for the excess risk of fracture in people with diabetes. We examined the predictive performance of FRAX without BMD in ethnically diverse, older patients with diabetes. Patients included were between ages 65-89 from the Kaiser Permanente Northern California Diabetes Registry and not already taking osteoporosis medications.

Bioinformatics and immunoinformatics approaches in the design of a multi-epitope vaccine targeting CTLA-4 for melanoma treatment.

Melanoma, a highly aggressive skin cancer, remains a significant cause of mortality despite advancements in therapeutic strategies. There is an urgent demand for developing vaccines that can elicit strong and comprehensive immune responses against this malignancy. Achieving this goal is crucial to enhance the efficacy of immunological defense mechanisms in combating this disease.

Use of Multimodal Artificial Intelligence in Surgical Instrument Recognition.

Accurate identification of surgical instruments is crucial for efficient workflows and patient safety within the operating room, particularly in preventing complications such as retained surgical instruments. Artificial Intelligence (AI) models have shown the potential to automate this process. This study evaluates the accuracy of publicly available Large Language Models (LLMs)-ChatGPT-4, ChatGPT-4o, and Gemini-and a specialized commercial mobile application, Surgical-Instrument Directory (SID 2.

Using Large Language Models to Retrieve Critical Data from Clinical Processes and Business Rules.

Current clinical care relies heavily on complex, rule-based systems for tasks like diagnosis and treatment. However, these systems can be cumbersome and require constant updates. This study explores the potential of the large language model (LLM), LLaMA 2, to address these limitations.

Challenges in practice and training structure of residents in obstetric anaesthesia: A perspective from teaching hospitals in Sindh province of Pakistan.

Objectives: To document information on the available obstetric anaesthesia services and structure of resident training in a Pakistani setting.

Methods: The survey was conducted from June to September 2018 across the Sindh province of Pakitan after approval from the ethics reiew committee of the Pakistan Society of Anaesthesiology, and covered all teaching hospitals in both public and private sectors recognised for residents' training for fellowship in Anaesthesiology by the College of Physician and Surgeons of Pakistan. A standardised questionnaire was filled by either the department chairperson or a senior designated faculty member in each institution regarding obstetric anaesthesia services and structure of resident training.