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

A retrospective case-control study from a single Chinese hospital built an internally validated machine learning model using ...

A DataCamp Machine Learning Project that predicts the best crop for a field using soil metrics through EDA, preprocessing, and classification models. - wncelrcn/Predictive-Modeling-for-Agriculture ...

A leakage-controlled benchmark of TabNet and eight baselines on cervical cancer and Alzheimer's disease miRNA datasets finds ...

IntroductionTo practice and master the machine learning I learned in class, I challenged myself to perform classification ...

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, ...

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 ...

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 = ...

When you start learning machine learning, you encounter many terms such as "features," "loss functions," "gradient descent," ...

Developing reliable machine learning models for health care can be challenging when only small datasets are available. This challenge motivates research into whether quantum computing approaches can ...