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Tea is among the most widely consumed drinks globally. Tea production is a key industry for many countries. One of the main challenges in tea harvesting is tea leaf diseases. If the spread of tea leaf diseases is not stopped in time, it can…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Omar Faruq Shikdar , Fahad Ahammed , B. M. Shahria Alam , Golam Kibria , Tawhidur Rahman , Nishat Tasnim Niloy

Background: The lack of explanations for the decisions made by algorithms such as deep learning has hampered their acceptance by the clinical community despite highly accurate results on multiple problems. Recently, attribution methods have…

Image and Video Processing · Electrical Eng. & Systems 2021-03-26 Amitojdeep Singh , J. Jothi Balaji , Mohammed Abdul Rasheed , Varadharajan Jayakumar , Rajiv Raman , Vasudevan Lakshminarayanan

Deep learning is quickly becoming the leading methodology for medical image analysis. Given a large medical archive, where each image is associated with a diagnosis, efficient pathology detectors or classifiers can be trained with virtually…

Computer Vision and Pattern Recognition · Computer Science 2017-06-28 Gwenolé Quellec , Katia Charrière , Yassine Boudi , Béatrice Cochener , Mathieu Lamard

Diabetic retinopathy (DR) is a complication of diabetes, and one of the major causes of vision impairment in the global population. As the early-stage manifestation of DR is usually very mild and hard to detect, an accurate diagnosis via…

Computer Vision and Pattern Recognition · Computer Science 2022-12-14 Yuhan Zheng , Fuping Wu , Bartłomiej W. Papież

Diabetic Retinopathy (DR) is a leading cause of vision loss globally. Yet despite its prevalence, the majority of affected people lack access to the specialized ophthalmologists and equipment required for assessing their condition. This can…

Computer Vision and Pattern Recognition · Computer Science 2021-10-22 Alexandros Papadopoulos , Fotis Topouzis , Anastasios Delopoulos

Type 1 diabetes (T1D) management can be significantly enhanced through the use of predictive machine learning (ML) algorithms, which can mitigate the risk of adverse events like hypoglycemia. Hypoglycemia, characterized by blood glucose…

Quantitative Methods · Quantitative Biology 2025-04-02 Beyza Cinar , Jennifer Daniel Onwuchekwa , Maria Maleshkova

Studies recently accomplished on the Enteric Nervous System have shown that chronic degenerative diseases affect the Enteric Glial Cells (EGC) and, thus, the development of recognition methods able to identify whether or not the EGC are…

Diabetes Mellitus is a metabolic disorder which may result in severe and potentially fatal complications if not well-treated and monitored. In this study, a quantitative analysis of the data collected using CGM (Continuous Glucose…

Quantitative Methods · Quantitative Biology 2023-08-15 Giulia Elena Aliffi , Giovanni Nastasi , Vittorio Romano , Dario Pitocco , Alessandro Rizzi , Elvin J. Moore , Andrea De Gaetano

This paper explores deterioration in Alzheimers Disease using Machine Learning. Subjects were split into two datasets based on baseline diagnosis (Cognitively Normal, Mild Cognitive Impairment), with outcome of deterioration at final visit…

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

INTRODUCTION: Advanced machine learning methods might help to identify dementia risk from neuroimaging, but their accuracy to date is unclear. METHODS: We systematically reviewed the literature, 2006 to late 2016, for machine learning…

Areas where Artificial Intelligence (AI) & related fields are finding their applications are increasing day by day, moving from core areas of computer science they are finding their applications in various other domains.In recent times…

Machine Learning · Computer Science 2016-07-19 Sahil Sharma , Vinod Sharma , Atul Sharma

Diabetic retinopathy (DR) is one of the major blindness-causing diseases currently known. Automatic grading of DR using deep learning methods not only speeds up the diagnosis of the disease but also reduces the rate of misdiagnosis.…

Image and Video Processing · Electrical Eng. & Systems 2023-05-25 Lei Shi , Bin Wang , Junxing Zhang

Fundus images are widely used for diagnosing various eye diseases, such as diabetic retinopathy, glaucoma, and age-related macular degeneration. However, manual analysis of fundus images is time-consuming and prone to errors. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Eric Shah , Jay Patel , Mr. Vishal Katheriya , Parth Pataliya

Diabetic retinopathy is a leading cause of vision loss among adults and a major global health challenge, particularly in underserved regions. This study presents PerceptronCARE, a deep learning-based teleophthalmology application designed…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Akwasi Asare , Isaac Baffour Senkyire , Emmanuel Freeman , Mary Sagoe , Simon Hilary Ayinedenaba Aluze-Ele , Kelvin Kwao

Major depressive disorder (MDD) is a heterogeneous condition; multiple underlying neurobiological substrates could be associated with treatment response variability. Understanding the sources of this variability and predicting outcomes has…

Deep learning has been successfully applied to a variety of image classification tasks. There has been keen interest to apply deep learning in the medical domain, particularly specialties that heavily utilize imaging, such as ophthalmology.…

Machine Learning · Computer Science 2019-02-13 Rony Gelman

Diabetic retinopathy (DR) and diabetic macular edema are common complications of diabetes which can lead to vision loss. The grading of DR is a fairly complex process that requires the detection of fine features such as microaneurysms,…

Computer Vision and Pattern Recognition · Computer Science 2020-06-09 Jonathan Krause , Varun Gulshan , Ehsan Rahimy , Peter Karth , Kasumi Widner , Greg S. Corrado , Lily Peng , Dale R. Webster

Vision-language models (VLMs) have demonstrated remarkable performance across a wide range of computer-vision tasks, sparking interest in their potential for digital health applications. Here, we apply VLMs to two fundamental challenges in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Victor Li , Naveenraj Kamalakannan , Avinash Parnandi , Heidi Schambra , Carlos Fernandez-Granda

An estimated 300 million people worldwide suffer from asthma, and this number is expected to increase to 400 million by 2025. Approximately 250,000 people die prematurely each year from asthma out of which, almost all deaths are avoidable.…

Computers and Society · Computer Science 2018-04-13 Saksham Kukreja

Cardiovascular disease and chronic kidney disease are major complications of diabetes, leading to high morbidity and mortality. Early detection of these conditions is critical, yet traditional diagnostic markers often lack sensitivity in…

Other Quantitative Biology · Quantitative Biology 2025-10-20 Syed Ibad Hasnain