AIMC Topic: Machine Learning

Clear Filters Showing 29231 to 29240 of 34417 articles

Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data.

Cancer reports (Hoboken, N.J.)
BACKGROUND: Breast cancer (BC) is a major global health concern with rising incidence and mortality rates in many developing countries. Effective BC risk assessment models are crucial for prevention and early detection. While the Gail model, a tradit...

Towards a unified framework for single-cell -omics-based disease prediction through AI.

Clinical and translational medicine
Single-cell omics has emerged as a powerful tool for elucidating cellular heterogeneity in health and disease. Parallel advances in artificial intelligence (AI), particularly in pattern recognition, feature extraction and predictive modelling, now of...

New opportunities and challenges for conservation evidence synthesis from advances in natural language processing.

Conservation biology : the journal of the Society for Conservation Biology
Addressing global environmental conservation problems requires rapidly translating natural and conservation social science evidence to policy-relevant information. Yet, exponential increases in scientific production combined with disciplinary differe...

Machine Learning Unveils Sphingolipid Metabolism's Role in Tumour Microenvironment and Immunotherapy in Lung Cancer.

Journal of cellular and molecular medicine
TME is a core player in the development of a cancerous lesion, the immune evasive potential of the lesion, and its response to therapy. Sphingolipid metabolism, which governs a number of cellular processes, has been recognised as a player involved in...

Determining health care cost drivers in older Hodgkin lymphoma survivors using interpretable machine learning methods.

Journal of managed care & specialty pharmacy
BACKGROUND: The cost of health care for patients with Hodgkin lymphoma (HL) is projected to rise, making it essential to understand expenditure drivers across different demographics, including the older adult population. Although older HL patients co...

Predicting In-Hospital Mortality in Patients With Acute Myocardial Infarction: A Comparison of Machine Learning Approaches.

Clinical cardiology
BACKGROUND: Acute myocardial infarction (AMI) remains a leading global cause of mortality. This study explores predictors of in-hospital mortality among AMI patients using advanced machine learning (ML) techniques.

The Shape of the Brain's Connections Is Predictive of Cognitive Performance: An Explainable Machine Learning Study.

Human brain mapping
The shape of the brain's white matter connections is relatively unexplored in diffusion magnetic resonance imaging (dMRI) tractography analysis. While it is known that tract shape varies in populations and across the human lifespan, it is unknown if ...

MoLPre: A Machine Learning Model to Predict Metastasis of cT1 Solid Lung Cancer.

Clinical and translational science
Given that more than 20% of patients with cT1 solid NSCLC showed nodal or extrathoracic metastasis, early detection of metastasis is crucial and urgent for improving therapeutic planning and patients' risk stratification in clinical practice. This st...

Artificial Intelligence Predicts Fitzpatrick Skin Type, Pigmentation, Redness, and Wrinkle Severity From Color Photographs of the Face.

Journal of cosmetic dermatology
BACKGROUND: Due to high patient demand, increasing numbers of non-dermatologists are performing skin assessments and carrying out laser interventions in medical spas, leading to inferior outcomes and higher complications. A machine learning tool that...

Comparative Evaluation of Pre-Test Probability Models for Coronary Artery Disease with Assessment of a New Machine Learning-Based Model.

Yonsei medical journal
PURPOSE: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model).