Keeping long-term climate simulations stable and accurate with a new AI approach

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...

Claude Opus 4.6 vs GPT-5.3-Codex: Which Agentic Coding Model Offers the Best Value

Anthropic's Claude Opus 4.6 and OpenAI's GPT-5.3-Codex go head-to-head in agentic coding, but are there any differences?

Range-resident logistic model connects animal movement and population dynamics

Despite decades of independent progress in population ecology and movement ecology, researchers have lacked a theoretical ...
Oncology Nurse Advisor

Intelligent Model Improves Accuracy of Radiation Dermatitis Grading

Suting emphasized that the tool could aid clinicians in timely and accurate grading of radiation dermatitis, thereby informing treatment adjustments and supportive care strategies. The use of an ...
News Medical

Early warning for diabetes: AI model identifies prediabetes risk with high accuracy

In a recent study published in the journal Scientific Reports, researchers developed a pattern neural network (PNN) model that combined a novel measure of total antioxidant status with traditional ...
Scientific Research Publishing

Spann, M. and Skiera, B. (2009) Sports Forecasting: A Comparison of the Forecast Accuracy of Prediction Markets, Betting Odds and Tipsters. Journal of Forecasting, 28, 55-72.

ABSTRACT: This paper evaluates the performance of multiple machine learning models in predicting NBA game outcomes. Both regression and classification approaches were explored, with models including ...
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 ...
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

Severity Classification of Freezing of Gait Using Machine-Learning Algorithms: A Hidden State Model Approach

Abstract: E-health sensors and wearables play an important role in the detection and classification of many chronic diseases. A chronic disease requires active monitoring and its severity increases ...
Frontiers

Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction

Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...