Advancing Neurological Disease Prediction through Machine Learning Techniques

A study explores how AI and ML can improve early detection of neurological diseases, including Parkinson’s disease, ...

New Study Reveals Powerful New Method Can Distinguish Schizophrenia from Healthy Using Brain SPECT Imaging

Reports demonstrates that whole-brain Single Photon Emission Computed Tomography (SPECT) imaging, combined with advanced ...

Innovative algorithm makes genomic surveillance faster and more affordable for global disease outbreaks

Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...

Optimizing RNA design with AI and an Ising machine: Encoding matters

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...
RMD Open

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still’s disease in fever of unknown origin: a retrospective …

Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
IEEE

LASSO-mCGA: Machine Learning and Modified Compact Genetic Algorithm-Based Biomarker Selection for Breast Cancer Subtype Classification

Abstract: Breast cancer is the most common cancer type among females and is one of the leading causes of death worldwide. Being a heterogeneous disease, subtyping breast cancer plays a vital role in ...
IEEE

Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions

Abstract: Malware has emerged as a cyber security threat that continuously changes to target computer systems, smart devices, and extensive networks with the development of information technologies.
TMCnet

Blockchain's First Fully Post-Quantum Transaction Just Settled on Mainnet. Here Is the Hash.

For a technical audience, the phrase that matters is "full stack." Post-quantum signatures have appeared on other networks. What has not shipped before, to the team's knowledge, is a live mainnet ...
Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
C&EN

Effect of Molecular Descriptor Feature Selection in Support Vector Machine Classification of Pharmacokinetic and Toxicological Properties of Chemical Agents

Department of Computational Science, National University of Singapore, Blk SOC1, Level 7, 3 Science Drive 2, Singapore 117543, Singapore-MIT Alliance, E-04-10, 4 Engineering Drive 3, Singapore, 117576 ...