NatureOpinion

Machine learning reveals potential consequences of cuts to US research

Governments have the right to decide how to spend money on science. Modelling shows that making instant cuts to grants ...
McKnight's Long-Term Care News

Simple screening questionnaires better for identifying social needs compared to advanced machine learning, study determines

Simple patient screening questionnaires addressing five different health-related social needs performed better than advanced machine learning methods at tracking HRSNs ...

Shaking up economic early warning systems with an artificial jellyfish algorithm

A study in the International Journal of Critical Infrastructures discusses a financial early warning system based on an ...
IEEE

Rainfall Classification Using Machine Learning Algorithms on Data Mining Platforms

Abstract: Weather conditions directly affect sectors such as agriculture and transport. With climate change, unpredictability is increasing and traditional calculation methods may not be sufficient.
Nanowerk

Optimized materials in a flash (w/video)

AutoBot platform combines machine learning and robotics to rapidly find the best ways to make advanced materials.
Tech Xplore

Autobot platform uses machine learning to rapidly find best ways to make advanced materials

A research team led by the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) has built and ...
Frontiers

Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm

1 School of Information Engineering, Anhui University of Chinese Medicine, Hefei, China 2 School of Pharmaceutical Economics and Management, Anhui University of Chinese Medicine, Hefei, China ...
IEEE

Comparative Analysis of Machine Learning Algorithms for BLE-Based Indoor Localization System

Abstract: Indoor positioning systems (IPS) play a vital role in applications such as navigation and asset tracking. This study presents a comprehensive evaluation of machine learning algorithms on a ...
Frontiers

Characterizing clinical risk profiles of major complications in type 2 diabetes mellitus using deep learning algorithms

Objective: To develop a self-reportable risk assessment tool for elderly type 2 diabetes mellitus (T2DM) patients, evaluating risks of diabetic nephropathy (DN), retinopathy (DR), peripheral ...