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Craniofacial anomalies indicate early developmental disturbances and are usually linked to many genetic syndromes. Early diagnosis is critical, yet ultrasound (US) examinations often fail to identify these features. This study presents an…

Image and Video Processing · Electrical Eng. & Systems 2024-09-05 Antonia Alomar , Ricardo Rubio , Laura Salort , Gerard Albaiges , Antoni Payà , Gemma Piella , Federico Sukno

Machine learning (ML) systems for medical imaging have demonstrated remarkable diagnostic capabilities, but their susceptibility to biases poses significant risks, since biases may negatively impact generalization performance. In this…

Machine Learning · Computer Science 2025-04-29 Haroui Ma , Francesco Quinzan , Theresa Willem , Stefan Bauer

Cervical adenocarcinoma in situ (AIS) is a critical premalignant lesion whose accurate histopathological diagnosis is challenging. Early detection is essential to prevent progression to invasive cervical adenocarcinoma. In this study, we…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Gabriela Fernandes

The interpretation of medical images is a challenging task, often complicated by the presence of artifacts, occlusions, limited contrast and more. Most notable is the case of chest radiography, where there is a high inter-rater variability…

For severely affected COVID-19 patients, it is crucial to identify high-risk patients and predict survival and need for intensive care (ICU). Most of the proposed models are not well reported making them less reproducible and prone to high…

Machine Learning · Computer Science 2024-03-29 Mahbubunnabi Tamala , Mohammad Marufur Rahmanb , Maryam Alhasimc , Mobarak Al Mulhimd , Mohamed Derichee

In intensive care units (ICUs), critically ill patients are monitored with electroencephalograms (EEGs) to prevent serious brain injury. The number of patients who can be monitored is constrained by the availability of trained physicians to…

Background: Coronary angiography (CAG) is a cornerstone imaging modality for assessing coronary artery disease and guiding interventional treatment decisions. However, in real-world clinical settings, angiographic images are often…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Jingsong Xia , Siqi Wang

A rapid and accurate diagnosis of cardiomegaly and pleural effusion is of the utmost importance to reduce mortality and medical costs. Artificial Intelligence has shown promise in diagnosing medical conditions. With this study, we seek to…

Image and Video Processing · Electrical Eng. & Systems 2022-11-08 Darlington Akogo , Benjamin Dabo Sarkodie , Issah Abubakari Samori , Bashiru Babatunde Jimah , Dorothea Akosua Anim , Yaw Boateng Mensah

Non-invasive and cost effective in nature, the echocardiogram allows for a comprehensive assessment of the cardiac musculature and valves. Despite progressive improvements over the decades, the rich temporally resolved data in…

The evaluation of obstructions (stenosis) in coronary arteries is currently done by a physician's visual assessment of coronary angiography video sequences. It is laborious, and can be susceptible to interobserver variation. Prior studies…

Image and Video Processing · Electrical Eng. & Systems 2021-02-01 Chengyang Zhou , Thao Vy Dinh , Heyi Kong , Jonathan Yap , Khung Keong Yeo , Hwee Kuan Lee , Kaicheng Liang

Purpose: Microsurgical Aneurysm Clipping Surgery (MACS) carries a high risk for intraoperative aneurysm rupture. Automated recognition of instances when the aneurysm is exposed in the surgical video would be a valuable reference point for…

Computer Vision and Pattern Recognition · Computer Science 2023-03-20 Jinfan Zhou , William Muirhead , Simon C. Williams , Danail Stoyanov , Hani J. Marcus , Evangelos B. Mazomenos

Atrial Fibrillation (AF) is among one of the most common types of heart arrhythmia afflicting more than 3 million people in the U.S. alone. AF is estimated to be the cause of death of 1 in 4 individuals. Recent advancements in Artificial…

Signal Processing · Electrical Eng. & Systems 2020-11-03 James Belen , Sajad Mousavi , Alireza Shamsoshoara , Fatemeh Afghah

Advances in machine learning have created new opportunities to develop artificial intelligence (AI)-based clinical decision support systems using past clinical data and improve diagnosis decisions in life-threatening illnesses such breast…

Human-Computer Interaction · Computer Science 2024-12-17 Olya Rezaeian , Onur Asan , Alparslan Emrah Bayrak

Background: The 2022 update of the Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound classification refines risk stratification for adnexal lesions, yet human interpretation remains subject to variability and conservative…

The adoption of diagnosis and prognostic algorithms in healthcare has led to concerns about the perpetuation of bias against disadvantaged groups of individuals. Deep learning methods to detect and mitigate bias have revolved around…

Optimal computations under uncertainty require an adequate probabilistic representation about beliefs. Deep generative models, and specifically Variational Autoencoders (VAEs), have the potential to meet this demand by building latent…

Predicting the long-term success of endovascular interventions in the clinical management of cerebral aneurysms requires detailed insight into the patient-specific physiological conditions. In this work, we not only propose numerical…

Coronary Computed Tomography Angiography (CCTA) evaluation of chest-pain patients in an Emergency Department (ED) is considered appropriate. While a negative CCTA interpretation supports direct patient discharge from an ED, labor-intensive…

Artificial intelligence (AI) has emerged as a powerful tool to enhance decision-making and optimize treatment protocols in in vitro fertilization (IVF). In particular, AI shows significant promise in supporting decision-making during the…

Image and Video Processing · Electrical Eng. & Systems 2024-12-30 Jana Zakall , Birgit Pohn , Antonia Graf , Daniel Kovatchki , Arezoo Borji , Ragib Shahriar Islam , Hossam Haick , Heinz Strohmer , Sepideh Hatamikia

Artificial intelligence (AI) systems accelerate medical workflows and improve diagnostic accuracy in healthcare, serving as second-opinion systems. However, the unpredictability of AI errors poses a significant challenge, particularly in…

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