Results 91 to 100 of about 7,493 (200)

Machine Learning for Predicting Colorectal Cancer‐Specific Mortality: The Role of Socioeconomic Inequalities in Public Policy

ANZ Journal of Surgery, EarlyView.
ABSTRACT Background Colorectal cancer remains a leading cause of mortality worldwide. We investigated whether adding socioeconomic information to machine learning models can improve the prediction of colorectal cancer‐specific mortality. Methods Using data from the Fundação Oncocentro de São Paulo (FOSP), we analyzed individuals diagnosed with ...
Felipe Mendes Delpino, Rocco Friebel, Francisco Tustumi, Marina Martins Siqueira, Gabriely Rangel Pereira, Marcelo Passos Teivelis, Lucas Hernandes Correa, Nelson Wolosker   +7 more
wiley   +1 more source

Automating Archaeological Discovery: Assessing Geospatial Artificial Intelligence (GeoAI) Tools for Stone Wall Identification in Kweneng, South Africa

Archaeometry, EarlyView.
ABSTRACT The discovery of archaeological sites traditionally entails the utilisation of physically demanding exploration methodologies, including terrain surveying and the analysis of historical records. Recent technological developments have led to an increased use of non‐invasive remote sensing techniques, including Google Earth, LiDAR and aerial ...
Mncedisi J. Siteleki
wiley   +1 more source

Machine Learning‐Based Prediction of Dental Caries in 12‐Year‐Old Adolescents: A Nationwide Cross‐Sectional Study in Korea

International Journal of Dental Hygiene, EarlyView.
ABSTRACT Objective We aimed to develop and evaluate machine learning models to support population‐level risk stratification for dental caries in the permanent dentition of 12‐year‐old Korean children and to visualise the relative importance of key predictors.
Gahyun Cho, Hae‐Young Kim, Ki‐Bong Choi, Sunmi Song, Junesun Kim   +4 more
wiley   +1 more source

EnsCL-CatBoost: A Strategic Framework for Software Requirements Classification

IEEE Access
Accurate classification of software requirements, distinguishing between functional and non-functional aspects, is crucial for developing reliable and efficient software systems. However, existing methods often struggle with insufficient semantic understanding and managing diverse software requirements.
Jalil Abbas, Cheng Zhang 0010, Bin Luo 0001   +2 more
openaire   +2 more sources

Machine Learning Methods for Forecasting Intermittent Tin Ore Production

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Effective production forecasting is important for resource planning and management in the mining industry. Tin ore production from Cutter Section Dredges (CSD) may fluctuate due to a variety of factors, in which there are periods when the production is ...
Nabila Dhia Alifa Rahmah, Budhi Handoko, Anindya Apriliyanti Pravitasari   +2 more
doaj   +1 more source

Multi‐Modal AI Approach in Depression Detection and Treatment: A Systematic Review of Last Decade

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Overview of multimodal approaches for depression detection and treatment. ABSTRACT Depression is a common and devastating mental health illness with serious personal and societal consequences. Despite advancing treatment techniques, there are still hurdles in the effective diagnosis and treatment of depression, such as prompt diagnosis, personalized ...
Smith K. Khare, Esmaeil S. Nadimi, U. Rajendra Acharya, Victoria Blanes‐Vidal   +3 more
wiley   +1 more source

Rectangular Concrete-Filled Steel Tube Rational Dimensions under Uniaxial Eccentric Compression

Structural Mechanics of Engineering Constructions and Buildings
An algorithm for generating the training dataset and the machine learning model for selecting the cross-sectional dimensions of eccentrically compressed concrete filled steel tubular (CFST) columns have been developed.
Anton S. Chepurnenko, Samir H. Al-Zgul, Batyr M. Yazyev   +2 more
doaj   +1 more source

Integrative Identification of Anti‐Photoaging Peptides From Stress‐Tolerant Microorganisms via Machine Learning and KEAP1–NRF2 Docking

Journal of Peptide Science, Volume 32, Issue 8, August 2026.
Novel short‐chain peptides targeting the KEAP1‐NRF2 axis were identified through a multimodal discovery platform combining a stress‐tolerant microbial library with machine learning and molecular docking. These peptides regulate collagen synthesis and reduce MMP1/9 levels in human fibroblasts, providing significant protection against photoaging ...
Hanui Lee, Gyeong Han Jeong, Ji Wan Choi, Taehwan Kim, Younhee Shin, Jaewon Lim, Kwang‐Woo Jung, Byung Yeoup Chung, Seung Sik Lee   +8 more
wiley   +1 more source

An interpretable machine learning-based framework for fatal traffic accident prediction and causal analysis

Digital Transportation and Safety
Traffic accidents are a leading cause of unnatural human fatalities. Numerous researchers have investigated ways to predict traffic fatalities and interpret the prediction results.
Zhuopeng Xie, Yongfeng Ma, Aemal J. Khattak, Shuyan Chen, Hongru Liu   +4 more
doaj   +1 more source

Hypertension Detection Using Explainable Stacked Ensemble Machine Learning From Clinical and Physiological Data: A Comprehensive Study

Health Science Reports, Volume 9, Issue 7, July 2026.
ABSTRACT Background and Aims Hypertension or high blood pressure is a life threatening common cardiovascular disease (CVD) all over the world. In the era of information technology, communication, and artificial intelligence, early prediction of hypertension using various techniques can be advantageous to alert patients.
Shah Muhammad Azmat Ullah, A. B. M. Aowlad Hossain, Md. Ebtidaul Karim   +2 more
wiley   +1 more source