We’re Ranking AI Models All Wrong And Why Human Capability Should Drive The Benchmark

At a moment when the AI industry is obsessed with bigger models and higher scores, Professor Ganna Pogrebna opened the ...
The Lancet

CARDBiomedBench: a benchmark for evaluating the performance of large language models in biomedical research

Although large language models (LLMs) have the potential to transform biomedical research, their ability to reason accurately across complex, data-rich domains remains unproven. To address this ...
Devdiscourse

Data-driven logistics can cut medical risk in disaster zones

A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...
Psychiatry Advisor

Accuracy of Machine Learning in Predicting CVD Risk in Bipolar Disease

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
Ophthalmology Advisor

ChatGPT Update May Identify Glaucoma From Clinical Images

The ChatGPT o1 Pro can accurately identify glaucoma from visual field and optical coherence tomography data, a study shows.
IEEE

A Hybrid CNN-Logistic Regression Model for Accurate Classification of Casting Defects

Abstract: The abstract is an imperfect defect detection model meant to classify various defects of castings. It presents an excellent precision, recall, and $\mathbf{F 1}$-score of six classes of ...
Live Science

Scientists just developed a new AI modeled on the human brain — it's outperforming LLMs like ChatGPT at reasoning tasks

The hierarchical reasoning model (HRM) system is modeled on the way the human brain processes complex information, and it outperformed leading LLMs in a notoriously hard-to-beat benchmark. When you ...
Scientific Research Publishing

Rahimloo, P. and Jafarian, A. (2016) Prediction of Diabetes by Using Artificial Neural Network, Logistic Regression Statistical Model and Combination of Them.

ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...
IEEE

Gender Classification from Facial Features Using Logistic Regression and K-Nearest Neighbors

Abstract: This paper presents a gender classification model based on face features using logistic regression and K-Nearest Neighbors (KNN) classifier. The dataset contained long hair, forehead breadth ...
Frontiers

Dynamic and static integrated classification model of gas well based on XGBoost algorithm—an example from block S of Sulige tight sandstone gas field

Classification of gas wells is an important part of optimizing development strategies and increasing the recovery. The original classification standard of gas wells in the Sulige gas field has weak ...
Frontiers

Automated classification of midpalatal suture maturation using 2D convolutional neural networks on CBCT scans

School of Dentistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada Introduction: Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, ...