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Event-based models (EBMs) infer disease progression from cross-sectional data, and standard EBMs assume a single underlying disease per individual. In contrast, mixed pathologies are common in neurodegeneration. We introduce the Joint…

Machine Learning · Computer Science 2026-01-14 Hongtao Hao , Joseph L. Austerweil

Objective Alzheimer disease (AD) is the most common cause of dementia, a syndrome characterized by cognitive impairment severe enough to interfere with activities of daily life. We aimed to conduct a systematic literature review (SLR) of…

Quantitative Methods · Quantitative Biology 2021-08-31 Sayantan Kumar , Inez Oh , Suzanne Schindler , Albert M Lai , Philip R O Payne , Aditi Gupta

Alzheimer's Disease (AD) ravages the cognitive ability of more than 5 million Americans and creates an enormous strain on the health care system. This paper proposes a machine learning predictive model for AD development without medical…

Quantitative Methods · Quantitative Biology 2020-06-17 Courtney Cochrane , David Castineira , Nisreen Shiban , Pavlos Protopapas

Background. Alzheimer's disease and related dementia (ADRD) are characterized by multiple and progressive anatomo clinical changes. Yet, modeling changes over disease course from cohort data is challenging as the usual timescales are…

Machine learning models have the potential to identify cardiovascular diseases (CVDs) early and accurately in primary healthcare settings, which is crucial for delivering timely treatment and management. Although population-based CVD risk…

The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that…

Progressive cognitive decline spanning across decades is characteristic of Alzheimer's disease (AD). Various predictive models have been designed to realize its early onset and study the long-term trajectories of cognitive test scores…

Plant diseases pose a significant threat to global food security, necessitating accurate and interpretable disease detection methods. This study introduces an interpretable attention-guided Convolutional Neural Network (CNN), CBAM-VGG16,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Balram Singh , Ram Prakash Sharma , Somnath Dey

Hip fractures are a leading cause of death and disability among older adults. Hip fractures are also the most commonly missed diagnosis on pelvic radiographs. Computer-Aided Diagnosis (CAD) algorithms have shown promise for helping…

Alzheimer's Disease (AD) is a severe brain disorder, destroying memories and brain functions. AD causes chronically, progressively, and irreversibly cognitive declination and brain damages. The reliable and effective evaluation of early…

Image and Video Processing · Electrical Eng. & Systems 2021-01-07 Kuo Yang , Emad A. Mohammed

Kidney stones are a common and debilitating health issue, and genetic factors play a crucial role in determining susceptibility. While Genome-Wide Association Studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs)…

Genomics · Quantitative Biology 2024-12-24 Amr Salem , Anirban Mondal

Non-communicable disease is the leading cause of death, emphasizing the need for accurate prediction of disease progression and informed clinical decision-making. Machine learning (ML) models have shown promise in this domain by capturing…

Machine Learning · Computer Science 2023-09-25 Zhoujian Sun , Wenzhuo Zhang , Zhengxing Huang , Nai Ding , Cheng Luo

Since February 2020, the world has been engaged in an intense struggle with the COVID-19 dis-ease, and health systems have come under tragic pressure as the disease turned into a pandemic. The aim of this study is to obtain the most…

Machine Learning · Computer Science 2022-06-30 Mehmet Tahir Huyut , Andrei Velichko

Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow obstruction. Current diagnostic methods primarily rely on identifying prominent features in spirometry (Volume-Flow time series) to detect…

Machine Learning · Computer Science 2025-03-04 Shuhao Mei , Xin Li , Yuxi Zhou , Jiahao Xu , Yong Zhang , Yuxuan Wan , Shan Cao , Qinghao Zhao , Shijia Geng , Junqing Xie , Shengyong Chen , Shenda Hong

The United States is experiencing an opioid epidemic, and there were more than 10 million opioid misusers aged 12 or older each year. Identifying patients at high risk of Opioid Use Disorder (OUD) can help to make early clinical…

The rise of Alzheimers Disease worldwide has prompted a search for efficient tools which can be used to predict deterioration in cognitive decline leading to dementia. In this paper, we explore the potential of survival machine learning as…

Machine Learning · Computer Science 2023-06-21 Henry Musto , Daniel Stamate , Ida Pu , Daniel Stahl

According to GHO (Global Health Observatory (GHO), the high prevalence of a large variety of diseases such as Ischaemic heart disease, stroke, lung cancer disease and lower respiratory infections have remained the top killers during the…

Artificial Intelligence · Computer Science 2020-09-17 Mayssa Ben Kahla , Dalel Kanzari , Ahmed Maalel

Atherosclerosis is one of the principle pathologies of cardiovascular disease with blood cholesterol a significant risk factor. The World Health Organisation estimates that approximately 2.5 million deaths occur annually due to the risk…

Tissues and Organs · Quantitative Biology 2015-10-08 Andrew Parton , Victoria McGilligan , Maurice OKane , Francina R Baldrick , Steven Watterson

The timely identification of significant memory concern (SMC) is crucial for proactive cognitive health management, especially in an aging population. Detecting SMC early enables timely intervention and personalized care, potentially…

Machine Learning · Computer Science 2024-05-31 M. Sajid , Rahul Sharma , Iman Beheshti , M. Tanveer

Age prediction using brain imaging, such as MRIs, has achieved promising results, with several studies identifying the model's residual as a potential biomarker for chronic disease states. In this study, we developed a brain age predictive…

Machine Learning · Computer Science 2025-04-22 Shahrzad Jamshidi , Arthur Bousquet , Sugata Banerji , Mark F. Conneely , Bita Aslrousta