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Related papers: An Approach to Intelligent Pneumonia Detection and…

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According to the World Health Organization (WHO), pneumonia is a disease that causes a significant number of deaths each year. In response to this issue, the development of a decision support system for the classification of patients into…

Image and Video Processing · Electrical Eng. & Systems 2025-03-06 Carlos Arizmendi , Jorge Pinto , Alejandro Arboleda , Hernando González

There is a growing demand for the use of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, particularly as clinical decision support systems to assist medical professionals. However, the complexity of many of these…

Human-Computer Interaction · Computer Science 2025-05-13 Dima Alattal , Asal Khoshravan Azar , Puja Myles , Richard Branson , Hatim Abdulhussein , Allan Tucker

The potential presented by Artificial Intelligence (AI) for healthcare has long been recognised by the technical community. More recently, this potential has been recognised by policymakers, resulting in considerable public and private…

Artificial Intelligence · Computer Science 2021-04-15 Jessica Morley , Caroline Morton , Kassandra Karpathakis , Mariarosaria Taddeo , Luciano Floridi

The main goal from this study is to discuss the main features of Artificial intelligence (AI) as well as their applicability for early cardiovascular Disease (CVDs) Detection, Material and Method : Systematic review approach Results : It…

Pneumonia, a respiratory infection brought on by bacteria or viruses, affects a large number of people, especially in developing and impoverished countries where high levels of pollution, unclean living conditions, and overcrowding are…

Image and Video Processing · Electrical Eng. & Systems 2024-09-02 Al Mohidur Rahman Porag , Md. Mahedi Hasan , Md Taimur Ahad

Artificial intelligence (AI) and specifically machine learning is making inroads into number of fields. Machine learning is replacing and/or complementing humans in a certain type of domain to make systems perform tasks more efficiently and…

Image and Video Processing · Electrical Eng. & Systems 2021-03-29 M. Abubakar , I. Shah , W. Ali , F. bashir

Artificial intelligence represents a new frontier in human medicine that could save more lives and reduce the costs, thereby increasing accessibility. As a consequence, the rate of advancement of AI in cancer medical imaging and more…

Mental health conditions cause a great deal of distress or impairment; depression alone will affect 11% of the world's population. The application of Artificial Intelligence (AI) and big-data technologies to mental health has great…

This research presents an innovative approach to cancer diagnosis and prediction using explainable Artificial Intelligence (XAI) and deep learning techniques. With cancer causing nearly 10 million deaths globally in 2020, early and accurate…

Artificial Intelligence · Computer Science 2024-12-24 Badaru I. Olumuyiwa , The Anh Han , Zia U. Shamszaman

Lung cancer remains one of the leading causes of morbidity and mortality worldwide, making early diagnosis critical for improving therapeutic outcomes and patient prognosis. Computer-aided diagnosis systems, which analyze computed…

Image and Video Processing · Electrical Eng. & Systems 2025-06-23 Guohui Cai , Ying Cai , Zeyu Zhang , Yuanzhouhan Cao , Lin Wu , Daji Ergu , Zhinbin Liao , Yang Zhao

According to the World Health Organization (WHO), air pollution kills seven million people every year. Outdoor air pollution is a major environmental health problem affecting low, middle, and high-income countries. In the past few years,…

Machine Learning · Computer Science 2024-01-04 Ihsane Gryech , Chaimae Assad , Mounir Ghogho , Abdellatif Kobbane

As the number of dementia patients rises, the need for accurate diagnostic procedures rises as well. Current methods, like using an MRI scan, rely on human input, which can be inaccurate. However, the decision logic behind machine learning…

Image and Video Processing · Electrical Eng. & Systems 2024-06-28 Tyler Morris , Ziming Liu , Longjian Liu , Xiaopeng Zhao

Diabetes is a major public health problem in the United States, affecting roughly 30 million people. Diabetes complications, along with the mental health comorbidities that often co-occur with them, are major drivers of high healthcare…

Quantitative Methods · Quantitative Biology 2019-09-19 Casey C. Bennett

Introduction: Artificial intelligence (AI) is exhibiting tremendous potential to reduce the massive costs and long timescales of drug discovery. There are however important challenges currently limiting the impact and scope of AI models.…

Other Quantitative Biology · Quantitative Biology 2024-09-25 Ghita Ghislat , Saiveth Hernandez-Hernandez , Chayanit Piyawajanusorn , Pedro J. Ballester

In modern dynamic constantly developing society, more and more people suffer from chronic and serious diseases and doctors and patients need special and sophisticated medical and health support. Accordingly, prominent health stakeholders…

Computers and Society · Computer Science 2022-08-10 Mirjana Ivanovic , Serge Autexier , Miltiadis Kokkonidis

The COVID-19 pandemic has forced many people to limit their social activities, which has resulted in a rise in mental illnesses, particularly depression. To diagnose these illnesses with accuracy and speed, and prevent severe outcomes such…

Machine Learning · Computer Science 2023-11-14 Hossein Simchi , Samira Tajik

Parkinson's disease (PD) is projected to increase substantially due to population aging, making early diagnosis increasingly important, as timely detection may delay progression and reduce long-term complications. Retinal microvasculature…

In the modern world, we are permanently using, leveraging, interacting with, and relying upon systems of ever higher sophistication, ranging from our cars, recommender systems in e-commerce, and networks when we go online, to integrated…

Artificial Intelligence · Computer Science 2023-06-23 Patrick Rodler

While previous studies have demonstrated the potential of AI to diagnose diseases in imaging data, clinical implementation is still lagging behind. This is partly because AI models require training with large numbers of examples only…