The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
IEEE

Enhancing Liver Cirrhosis Diagnosis Using Machine Learning With Explainable AI and Cross-Validated Hyperparameter Tuning Techniques

Abstract: Cirrhosis is a form of Chronic Liver Disease (CLD) resulting from sustained liver damage from several causes, including viral infection, autoimmune disorders, cholestatic and metabolic ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
BMJ

Advancing Alzheimer’s disease risk prediction: development and validation of a machine learning-based preclinical screening model in a cross-sectional study

Objectives Alzheimer’s disease (AD) poses a significant challenge for individuals aged 65 and older, being the most prevalent form of dementia. Although existing AD risk prediction tools demonstrate ...
BMJ

Development and validation of a machine learning-based prediction model for frailty in older adults with diabetes: a study protocol for a retrospective cohort study

Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...
IEEE

LYRICEL: Knowledge Graphs Combined With Large Language Models and Machine Learning for Cross-Cultural Analysis of Lyrics—The Case of Greek Songs

Abstract: This paper presents LYRICEL, a framework integrating Knowledge Graph (KG) representation learning, Large Language Models (LLMs), and machine learning for reliable, explainable, and ...
Frontiers

Development and validation of novel machine learning-based prognostic models and propensity score matching for comparison of surgical approaches in mucinous breast cancer

1 Department of Breast, Jiangmen Central Hospital, Jiangmen, Guangdong, China 2 The Breast Center, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China Mucinous breast ...
marktechpost

A Coding Implementation to Build an AI Agent with Live Python Execution and Automated Validation

In this tutorial, we will discover how to harness the power of an advanced AI Agent, augmented with both Python execution and result-validation capabilities, to tackle complex computational tasks. By ...
The New York Times

A Hot Accessory, at the Intersection of Faith and Culture

Seen on influencers, pop stars and White House staff, cross necklaces are popping up everywhere. By Misty White Sidell When Arianna Salerno first moved to Washington, D.C., in 2022 to attend Catholic ...
jnis.bmj

Development and validation of an explainable machine learning prediction model for futile recanalization after mechanical thrombectomy in acute large vessel occlusion stroke

Background Mechanical thrombectomy (MT) is the primary treatment for acute ischemic stroke (AIS) caused by large vessel occlusion (LVO). However, the likelihood of futile recanalization (FR) at 90 ...