Disulfidptosis-Related Gene Signature Predicts 28-Day Mortality in Sepsis: A Multi-Cohort, Multi-Evidence Study Integrating Mendelian Randomization, Machine Learning, and Systematic Drug Repurposing

M3SpaDE: A Multi-Modal Deep Learning Framework for Predicting Spatially Resolved Drug Responses

Zihao Zhang, Xinyu Cui, Zhengke Lian, Xiufeng Pang, Ye, Youqiong, Jiang, Cizhong

M3SpaDE (Multi-Modal Model for predicting Spatial Drug Efficacy) is a versatile computational framework designed for predicting drug sensitivity in spatial transcriptomics data. It is resolution-agnostic, capable of processing data ranging from single-cell to spot-level resolutio…Read more

Also available via: European Organization for Nuclear Research

A Systematic Review of Machine Learning, Deep Learning, and Explainable AI Approaches for Cardiac Disease Prediction

Sunanda Budihal, Sheetalrani Kawale, Abhishek Angadi

The cardiovascular (Cardiac) disease (CVD) is another factor that causes death among the global population most, and this is the reason why there is a high necessity to implement proper, effective, and interpretive diagnostic systems. The usage of machine learning (ML), deep lear…Read more

Also available via: European Organization for Nuclear Research

Predictive Maintenance of Power Transformers using Machine Learning- A Case Study

AMANING RICHMOND OFORI, Electronic Engineering, DR JOSEPH C. ATTACHIE

The importance of power transformers in electrical power systems cannot be overstated, as their failures can lead to considerable economic losses and disruptions. The typical malfunctions encountered by a power transformer comprise dielectric issues, thermal losses due to copper…Read more

Integrating ToF-SIMS and machine learning reveals a mammary tumor-associated multi-ion signature — analysis code

Auraya Manaprasertsak, Wei Tang, Caroline Lööf, Laila Azemovic, Sofie Mohlin, Catharina Hagerling, et al.

Analysis code, result tables, and figures for a time-of-flight secondary ion mass spectrometry (ToF-SIMS) machine-learning study of a mammary tumor-associated multi-ion signature and its detectability across biological samples in the MMTV-PyMT mouse model of breast cancer. Accomp…Read more

Raw spectra for Integrating ToF-SIMS and machine learning reveals a mammary tumor-associated multi-ion signature

Auraya Manaprasertsak, Wei Tang, Caroline Lööf, Laila Azemovic, Sofie Mohlin, Catharina Hagerling, et al.

Financial Distress Prediction in Mature Markets: A Machine Learning Approach across G7 Economies

Varunn Kaushik

Abstract: This study examines the determinants and predictive accuracy of financial distress for seven mature market economies: Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States. The aim is to assess whether distress can be predicted through a unifo…Read more