AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
The Banker

Banks and regulators clash over ‘black box’ AI credit risk

Earlier this year when a UK Treasury Committee released a report warning that regulators’ complacency on AI in financial ...
Analytics Insight

How Machine Learning Works: Step-by-Step Explained

Machine learning powers modern AI systems through data analysis, pattern recognition, training, testing, and continuous optimization. Industries increasingly use machine learning to automate tasks, ...
IEEE

A Review and Experimental Comparison of Multivariate Decision Trees

Abstract: Decision trees are popular as stand-alone classifiers or as base learners in ensemble classifiers. Mostly, this is due to decision trees having the advantage of being easy to explain. To ...
BMJ

Evidence-based detection of pulmonary arterial hypertension in systemic sclerosis: the DETECT study

Objective Earlier detection of pulmonary arterial hypertension (PAH), a leading cause of death in systemic sclerosis (SSc), facilitates earlier treatment. The objective of this study was to develop ...
IEEE

Algorithm of Building Regression Decision Tree Using Complementary Features

Abstract: In the so-called explained artificial intelligence, there is a need to build small models, but accurate and intuitive for the analyst. It is necessary to formalize, which models are ...
LinkedIn

The Architecture of Agentic AI: Key Components Explained

Lieutenant Commander Geordi La Forge is one of my favorite characters from Star Trek: The Next Generation. As the chief engineer of the USS Enterprise, La Forge is responsible for maintaining the ship ...
El País in English

AI’s black box problem: Why is it still indecipherable to researchers

Some artificial intelligence algorithms, particularly neural networks, have internal processes that remain largely unknown. This lack of transparency is one of the sources of biases and hallucinations ...
ascopubs.org

Employing machine learning (ML) and explainable artificial intelligence (XAI) to predict and explain suicidal ideation among patients with prostate cancer.

The outcome of COVID-19 infection among Saudi oncology patients. This is an ASCO Meeting Abstract from the 2024 ASCO Annual Meeting I. This abstract does not include a full text component.
LinkedIn

K-Nearest Neighbors (KNN) Algorithm for Classification: Real-world Applications and Examples

K-Nearest Neighbors (KNN) is a simple yet effective supervised machine learning algorithm used for both regression and classification tasks. The algorithm works by finding the K nearest data points in ...
Nature

Automated discovery of algorithms from data

Human reasoning discovers principles from the world and systematizes them into rule-based knowledge such as mathematical equations, medical treatment protocols, chemical synthesis pathways and ...
Nature

Improved adaptive-phase fuzzy high utility pattern mining algorithm based on tree-list structure for intelligent decision systems

With the rapid development of AI and big data mining technologies, computerized medical decision-making has become increasingly prominent. The aim of high-utility pattern mining (HUPM) is to discover ...