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The medical field stands to see significant benefits from the recent advances in deep learning. Knowing the uncertainty in the decision made by any machine learning algorithm is of utmost importance for medical practitioners. This study…

Machine Learning · Statistics 2017-06-06 Jos van der Westhuizen , Joan Lasenby

Medical image analysis has emerged as an essential element of contemporary healthcare, facilitating physicians in achieving expedited and precise diagnosis. Recent breakthroughs in deep learning, a subset of artificial intelligence, have…

Image and Video Processing · Electrical Eng. & Systems 2024-11-06 Aimina Ali Eli , Abida Ali

Medical image classification is crucial for diagnosis and treatment, benefiting significantly from advancements in artificial intelligence. The paper reviews recent progress in the field, focusing on three levels of solutions: basic,…

Image and Video Processing · Electrical Eng. & Systems 2025-06-06 Loan Dao , Ngoc Quoc Ly

A main driver behind the digitization of industry and society is the belief that data-driven model building and decision making can contribute to higher degrees of automation and more informed decisions. Building such models from data often…

Machine learning is used in medicine to support physicians in examination, diagnosis, and predicting outcomes. One of the most dynamic area is the usage of patient generated health data from intensive care units. The goal of this paper is…

The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Paschalis Bizopoulos , Dimitrios Koutsouris

The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected data, and the identification of promising research directions.…

Computation and Language · Computer Science 2016-07-19 Victor Andrei , Ognjen Arandjelovic

Artificial Intelligence (AI) is revolutionizing emergency medicine by enhancing diagnostic processes and improving patient outcomes. This article provides a review of the current applications of AI in emergency imaging studies, focusing on…

Image and Video Processing · Electrical Eng. & Systems 2025-03-20 Gustavo Correia , Victor Alves , Paulo Novais

Machine learning has long since become a keystone technology, accelerating science and applications in a broad range of domains. Consequently, the notion of applying learning methods to a particular problem set has become an established and…

The science of solving clinical problems by analyzing images generated in clinical practice is known as medical image analysis. The aim is to extract information in an effective and efficient manner for improved clinical diagnosis. The…

Computer Vision and Pattern Recognition · Computer Science 2019-05-22 Syed Muhammad Anwar , Muhammad Majid , Adnan Qayyum , Muhammad Awais , Majdi Alnowami , Muhammad Khurram Khan

Machine Learning has been applied to pathology images in research and clinical practice with promising outcomes. However, standard ML models often lack the rigorous evaluation required for clinical decisions. Machine learning techniques for…

Image and Video Processing · Electrical Eng. & Systems 2022-04-19 Syed Ashar Javed , Dinkar Juyal , Zahil Shanis , Shreya Chakraborty , Harsha Pokkalla , Aaditya Prakash

In the pharmaceutical industry, the use of artificial intelligence (AI) has seen consistent growth over the past decade. This rise is attributed to major advancements in statistical machine learning methodologies, computational capabilities…

Methodology · Statistics 2023-12-01 Yuhan Li , Hongtao Zhang , Keaven Anderson , Songzi Li , Ruoqing Zhu

Many of the current scientific advances in the life sciences have their origin in the intensive use of data for knowledge discovery. In no area this is so clear as in bioinformatics, led by technological breakthroughs in data acquisition…

Machine Learning · Computer Science 2018-02-28 Davide Bacciu , Paulo J. G. Lisboa , José D. Martín , Ruxandra Stoean , Alfredo Vellido

The increasing popularity of attention mechanisms in deep learning algorithms for computer vision and natural language processing made these models attractive to other research domains. In healthcare, there is a strong need for tools that…

Computer Vision and Pattern Recognition · Computer Science 2022-04-27 Tiago Gonçalves , Isabel Rio-Torto , Luís F. Teixeira , Jaime S. Cardoso

Many healthcare decisions involve navigating through a multitude of treatment options in a sequential and iterative manner to find an optimal treatment pathway with the goal of an optimal patient outcome. Such optimization problems may be…

Machine Learning · Computer Science 2021-03-10 Elsa Riachi , Muhammad Mamdani , Michael Fralick , Frank Rudzicz

Machine learning is a rapidly growing field with the potential to revolutionize many areas of science, including physics. This review provides a brief overview of machine learning in physics, covering the main concepts of supervised,…

Machine Learning · Computer Science 2023-10-17 Francisco A. Rodrigues

Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret…

Automated industries lead to high quality production, lower manufacturing cost and better utilization of human resources. Robotic manipulator arms have major role in the automation process. However, for complex manipulation tasks, hard…

Artificial Intelligence is providing astonishing results, with medicine being one of its favourite playgrounds. In a few decades, computers may be capable of formulating diagnoses and choosing the correct treatment, while robots may perform…

In countries that enabled patients to choose their own providers, a common problem is that the patients did not make rational decisions, and hence, fail to use healthcare resources efficiently. This might cause problems such as overwhelming…

Computers and Society · Computer Science 2020-06-25 Lichin Chen , Yu Tsao , Ji-Tian Sheu