TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...
Medical News Today

AI model may identify high-risk patients for post-transplant complications

A recent study suggests that a freely available AI tool could help predict dangerous complications after stem cell transplants.
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 ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
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 ...
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 ...