Medical Dialogues

AI Potential in Transforming Management of Hematologic Malignancies- Latest Cureus Review

A recent review concluded that artificial intelligence (AI) is rapidly transforming the diagnosis and treatment of haematological malignancies by enhancing diagnostic accuracy and ...
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...
Devdiscourse

Data-driven AI approach narrows diagnostic gap between dengue and chikungunya

Dengue and chikungunya, the two mosquito-borne diseases that frequently circulate at the same time, share the same Aedes ...
IEEE

Leveraging Machine Learning Algorithms for Diabetes Prediction

Abstract: This paper analyzes the performance of different LDA combinations with machine learning algorithms in predicting diabetes based on clinical data. The analysis involves patient records with ...
GitHub

RFX-Fuse: Breiman and Cutler's Random Forests as a Forest Unified Learning and Similarity Engine - Extended with Native Explainable Similarity

RFX-Fuse (Random Forests X [X=compression] — Forest Unified Learning and Similarity Engine) delivers Breiman and Cutler's complete vision for Random Forests as a Forests Unified Machine Learning and ...
Oak Ridge National Lab

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial ...
Frontiers

Multi-feature integrated machine learning prediction model for early nephropathy in elderly living with type 2 diabetes mellitus

Aims: To develop and validate a multi-feature machine learning (ML) model for early diabetic nephropathy (DN) prediction in elderly living with type 2 diabetes mellitus (T2DM), incorporating clinical ...
Frontiers

Development and validation of an interpretable machine learning model for predicting cognitive impairment in patients with sepsis

1 Department of Critical Care Medicine, Shenzhen Baoan Shiyan People’s Hospital, Shenzhen, China 2 Department of Gynecology, Langxin Community Health Service Center, Shenzhen Baoan Shiyan People’s ...
IEEE

A Comparative Analysis of Machine Learning Algorithms for Diabetes Prediction Using Numerical-to-Image Data Transformation

Abstract: Diabetes is a global health issue that requiring early detection to prevent life-threatening complications. This study compares several machine learning models for predicting diabetes using ...
Medical Xpress

Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...