arXiv Machine Learning September 22, 2026 By Md Ahshanul Haque, Muhammad Ashad Kabir

Machine Learning-Based Prediction of Childhood Stunting in Bangladesh: Fairness and Temporal Robustness Assessment

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arXiv Machine Learning

Jun 16

Temporal Validation Changes the Apparent Public-Health Utility of Under-Five Mortality Prediction in Bangladesh: A Four-Round DHS Machine-Learning Study

arXiv:2602. 03957v2 Announce Type: replace Abstract: Background: Under-five mortality in Bangladesh remains uneven despite national progress.

By Md Muhtasim Munif Fahim, M. Monimul Huq, M. Sabiruzzaman, Md Rezaul Karim

arXiv Machine Learning

Jul 28

Deep learning approaches show promise for predicting childhood malnutrition: A comparative study with traditional machine learning methods using survey data

arXiv:2602. 10381v2 Announce Type: replace Abstract: Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches are labor-intensive and frequently unavailable in remote areas.

By Deepak Bastola, Yang Li

arXiv Machine Learning

Jul 21

Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis

arXiv:2607. 17024v1 Announce Type: new Abstract: Air pollution and climate-related stressors are increasingly important concerns for respiratory health, especially in settings with unequal environmental exposure and healthcare capacity.

By Maede Azani Hassan Abadi, Shouyi Wang

arXiv AI

Jul 21

Comprehensive Evaluation of Machine Learning for Type 2 Diabetes Risk Prediction: Large-Scale External Validation and Fairness Analysis

arXiv:2607. 16253v1 Announce Type: cross Abstract: Machine learning-based Type 2 diabetes risk prediction models obtain good internal validation results but lose effectiveness in real-world applications due to deficient external testing and fairness assessment.

By Rajveer Singh Pall, Sameer Yadav, Siddharth Bhalerao, Sourabh Sahu, Ritu Ahluwalia, Bhaskar Awadhiya

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arXiv Machine Learning

Jun 2

Early Prediction of Liver Cirrhosis Up to Two Years in Advance: A Machine Learning Study Benchmarking Against the FIB-4 and APRI Scores

arXiv:2601. 00175v2 Announce Type: replace Abstract: Objective: Develop and evaluate machine learning (ML) models for predicting incident liver cirrhosis (LC) one and two years prior to diagnosis using routinely collected electronic health record (EHR) data and benchmark their performance against the FIB-4 and APRI clinical scores.

By Zhuqi Miao, Ahmed G Qasem, Sujan Ravi, Jason T. Cheng, Abdulaziz Ahmed, Courtney W. Houchen, Sumayah Abed, Dilorom Azimdjanovna Zuparova, Abdulaziz Ahmed

benchmarks

arXiv Machine Learning

Aug 24

Machine Learning and ARIMA Model Averaging for Adaptive Public Health Forecasting: Comparative Evaluation and an Ontario COVID-19 Case Study

arXiv:2608.20406v1 Announce Type: new Abstract: Public health forecasts must respond to abrupt changes in surveillance data without over-extrapolating noise, reporting artifacts, or temporary trends....

By Yushu Zou, Ye Li, Johra Moosa, Martin Grunnill, Samir N. Patel, Venkata R. Duvvuri

One email a morning, machine-written

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Temporal Validation Changes the Apparent Public-Health Utility of Under-Five Mortality Prediction in Bangladesh: A Four-Round DHS Machine-Learning Study

Deep learning approaches show promise for predicting childhood malnutrition: A comparative study with traditional machine learning methods using survey data

Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis

Comprehensive Evaluation of Machine Learning for Type 2 Diabetes Risk Prediction: Large-Scale External Validation and Fairness Analysis

Early Prediction of Liver Cirrhosis Up to Two Years in Advance: A Machine Learning Study Benchmarking Against the FIB-4 and APRI Scores

Machine Learning and ARIMA Model Averaging for Adaptive Public Health Forecasting: Comparative Evaluation and an Ontario COVID-19 Case Study