Communications of the ACMOpinion

Rolling in the Deep of Cognitive and AI Biases

To address AI bias at its roots, we must understand the human heuristics that shape it. Unlike prior frameworks that focus ...
Genomics England

Genomic Data Scientist in Rare Disease (we have office locations in Cambridge, Leeds & London)

Job Description We are seeking a passionate and innovative Genomic Data Scientist to join our cutting-edge team.  You will work in ...
chromatographyonline

Optimizing HSSE-GC-MS and Machine Learning for Forensic Gender Classification from Human Scent

Researchers have optimized a headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry (GC-MS) to analyze human scent traces left on clothing. By extracting ...
IEEE

An Approach to Attack Classification for Programmable Network Infrastructure Using Machine Learning and Deep Learning Solutions

Abstract: The rapid development of Internet-connected devices has driven the rise of smart cities, where large-scale Internet of Things (IoT) systems require efficient infrastructure management with ...
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
Scientific Research Publishing

A Wind Speed Prediction Model Based on Machine Learning in Guyuan Area ()

1 School of Atmospheric Sciences, Chengdu University of Information and Technology, Chengdu, China. 2 Guyuan Meteorological Bureau, Guyuan, China. 3 Jilin Provincial Institute of Meteorological ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
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 = ...
Frontiers

Explainable machine learning model for predicting the outcome of acute ischemic stroke after intravenous thrombolysis

Acute ischemic stroke (AIS) patients often experience poor functional outcomes post-intravenous thrombolysis (IVT). Novel computational methods leveraging machine learning (ML) architectures ...
Frontiers

An explainable machine learning model for predicting chronic coronary disease and identifying valuable text features

Chronic Coronary Disease (CCD) is a leading global cause of morbidity and mortality. Existing Pre-test Probability (PTP) models mainly rely on in-hospital data and clinician judgment. This study aims ...