BIOENGINEER

Blood Test Model Built with Machine Learning Distinguishes First-Episode Schizophrenia from Healthy Controls

A retrospective case-control study from a single Chinese hospital built an internally validated machine learning model using ...
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 models predict severe chemotherapy-induced neutropenia in breast cancer using only pre-treatment data

Machine learning models built only from pre-chemotherapy data predicted severe neutropenia in breast cancer patients with ...
ascopubs.org

Error Reduction in Leukemia Machine Learning Classification With Conformal Prediction

Assessing Algorithmic Fairness With a Multimodal Artificial Intelligence Model in Men of African and Non-African Origin on NRG Oncology Prostate Cancer Phase III Trials Recent advances in machine ...

[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 ...
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
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 ...
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, ...

Label Design in Financial Machine Learning: Triple Barrier Method, Meta-Labeling, and Pitfalls of Prediction Accuracy

In quantitative trading research, a significant amount of time is spent on model architecture, feature engineering, and ...