European Medical Journal

Machine Learning Shows Promise for Alzheimer’s Classification

Machine learning for Alzheimer’s disease classification achieved up to 88.1% accuracy using clinical data, but external ...
BIOENGINEER

Machine learning with patient words sharpens emergency triage classification

A retrospective cohort study of 64,382 adult emergency department patients in Brazil found that adding natural language ...
Nature

Feature Selection Techniques in Machine Learning Systems articles from across Nature Portfolio

Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS for HSIs remains ...
BIOENGINEER

Retrospective machine learning models predict amputation risk in diabetic arterial disease

A retrospective multicenter study of 1,919 Chinese patients found that a 14-predictor gradient-boosting model achieved an AUC ...
techtarget

4 types of machine learning models explained

Artificial intelligence is built on the foundation of machine learning (ML) models. These models are software programs designed to classify data, identify data patterns, spot anomalies in data sets, ...

[Part 3] Predicting Numbers or Choosing Categories?: A Gentle Explanation of Regression and Classification

Estimated reading time: approx. 3 minutes 30 secondsIn machine learning, models learned from past data are used to predict the results of new data. These predictions are broadly divided into ...
Analytics Insight

What Should an AI/ML Beginner Learn First: Python, Machine Learning or Generative AI?

Overview: Learn programming fundamentals, data handling, libraries, and API integration before tackling advanced AI ...

Evaluation of Drug-Drug Interactions and AI: How to Use Predictive Models Under ICH M12

Hello.This is Pharmer.In the previous article, "How Far Can Machine Learning Be Used to Predict Protein Binding Rates?", we ...
techtarget

How to ensure interpretability in machine learning models

Creating machine learning models that generate accurate results is one thing, but it's quite another to ensure model interpretability -- the ability to understand why the ML models that power AI tools ...