Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,501 to 1,510 of 213,568 articles

Quality by Design to Mitigate Aggregation: Mechanistic Insights and Analytical Strategies for Biopharmaceutical Manufacturing.

Therapeutic innovation & regulatory science
This review highlights the problem of protein molecule aggregation, which represents a significant challenge in the field of biopharmaceuticals. Protein aggregation is critical because it can affect the efficacy and safety of biopharmaceuticals, incl... read more 

Precision Medicine for Anticoagulation Strategies in the Cath Lab: Part 2.

Current cardiology reports
PURPOSE OF REVIEW: Intraprocedural anticoagulation during percutaneous coronary intervention (PCI) remains particularly challenging in high-risk and underrepresented populations, where the balance between thrombotic and bleeding risk is complex and o... read more 

Changes in collateral status during transfer for thrombectomy are predictive of functional outcome in large vessel occlusion stroke.

GeroScience
Collateral circulation that determines infarct progression in large vessel occlusion (LVO) is implicitly regarded as stationary. We investigated collateral circulation changes during interfacility transfer for endovascular thrombectomy (EVT) and its ... read more 

Metabolic signatures of triple-negative breast cancer.

Molecular biology reports
Triple-negative breast cancer (TNBC), being one of the most aggressive subtypes of breast malignancies, is characterized by poor prognosis and limited treatment options. As a leading cause of cancer-related mortality among women, TNBC poses unique cl... read more 

An interpretable machine learning model integrating ultrasound and clinical variables for predicting osteoporosis in patients with rheumatoid arthritis.

Clinical rheumatology
OBJECTIVES: Rheumatoid arthritis (RA) significantly increases the risk of osteoporosis (OP) and fractures, yet dual-energy X-ray absorptiometry (DXA) is underused in routine care. This study aims to develop and explain a machine learning model to ide... read more 

Differentiating septic arthritis from non-infectious inflammatory causes of acute monoarticular arthritis in children: A machine learning approach based on routine laboratory tests.

Irish journal of medical science
OBJECTIVE: Acute monoarthritis in children poses a diagnostic challenge, particularly in distinguishing septic arthritis from non-infectious inflammatory causes. Delayed or incorrect diagnosis may lead to serious complications or inappropriate treatm... read more 

Interpretable machine-learning survival prediction of breast cancer prognosis from lifestyle factors: evidence from UK biobank.

Breast cancer (Tokyo, Japan)
BACKGROUND: Understanding how lifestyle habits influence breast cancer survival is crucial for improving long-term outcomes and guiding individualized care. The purpose of this study is to comprehensively understand how dietary habits, exercise frequ... read more 

Understanding Harm Generated by Analytic Technique Bias from the Afro-communitarian Perspective.

The New bioethics : a multidisciplinary journal of biotechnology and the body
This primarily normative article draws on three ideas - exclusivism, (transformative) inclusivism and incompleteness/conviviality - grounded in Afro-communitarian thinking - to argue that isolation/alienation, minimization, and essentialism are three... read more 

Artificial intelligence assessment of endoscopic severity and extent: A machine learning approach to continuous evaluation of endoscopic inflammation in ulcerative colitis.

Inflammatory bowel diseases
BACKGROUND: The endoscopy subscore is a therapeutic endpoint in ulcerative colitis trials but is limited by reader variability and inability to fully capture the degree of inflammation across the colon. We developed the artificial intelligence assess... read more