Automated Machine Learning Market to Grow at a Robust CAGR of 45.90%, Crossing USD 35.5 Billion by 2032 Amid Rapid Enterprise AI Adoption | AnalystView Market In…

North America Captures a Significant Revenue Share in the Automated Machine Learning Market, Supported by Government-Backed ...
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
TMCnet

How to Hire Python Developers in 2026 - The Complete Guide (for Startups & Scaleups)

Python''s popularity is surging. In 2025, it achieved a record 26.14% TIOBE index rating, the highest any language has ever ...
BMJ Open

Development and evaluation of a diagnostic aiding tool for differentiating tropical fevers using artificial intelligence approach: a study protocol from tertiary care hospital ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
GitHub

ECS7020P Principles of Machine Learning - Mini Project

This repository contains the mini project for the ECS7020P Principles of Machine Learning course at Queen Mary University of London. This project develops an automated song recognition system capable ...
Frontiers

Comparative analysis of machine learning techniques on the BraTS dataset for brain tumor classification

1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...
Scientific Research Publishing

Razavi, M., Ziyadidegan, S., Jahromi, R., et al. (2023) Machine Learning, Deep Learning and Data Preprocessing Techniques for Detection, Prediction, and Monitoring of Stress ...

ABSTRACT: Mood disorders—particularly bipolar spectrum conditions—pose enduring diagnostic and therapeutic challenges due to their episodic nature, heterogeneous presentations, and reliance on ...
IEEE

A Self-Adaptive Data Preprocessing Pipeline for Machine Learning: An Automated and Dynamic Approach

Abstract: The optimization and generalization of performance of a machine learning model is profoundly influenced by efficient data preprocessing. A machine's learning model does not perform to its ...