Related papers: EvoCLINICAL: Evolving Cyber-Cyber Digital Twin wit…
The Cancer Registry of Norway (CRN) collects and processes cancer-related data for patients in Norway. For this, it employs a sociotechnical software system that evolves with changing requirements and medical standards. The current practice…
The Cancer Registry of Norway (CRN) collects, curates, and manages data related to cancer patients in Norway, supported by an interactive, human-in-the-loop, socio-technical decision support software system. Automated software testing of…
The Cancer Registry of Norway (CRN) is a public body responsible for capturing and curating cancer patient data histories to provide a unified access to research data and statistics for doctors, patients, and policymakers. For this purpose,…
The Cancer Registry of Norway (CRN) is a part of the Norwegian Institute of Public Health (NIPH) and is tasked with producing statistics on cancer among the Norwegian population. For this task, CRN develops, tests, and evolves a software…
The Cancer Registration Support System (CaReSS), built by the Cancer Registry of Norway (CRN), is a complex real-world socio-technical software system that undergoes continuous evolution in its implementation. Consequently, continuous…
Neuro-oncological prognostics are now vital in modern clinical neuroscience because brain tumors pose significant challenges in detection and management. To tackle this issue, we propose a cognitive digital twin framework that combines…
Advances in classical machine learning and single-cell technologies have paved the way to understand interactions between disease cells and tumor microenvironments to accelerate therapeutic discovery. However, challenges in these machine…
Artificial Intelligence (AI) and Large Language Models (LLMs) hold significant promise in revolutionizing healthcare, especially in clinical applications. Simultaneously, Digital Twin technology, which models and simulates complex systems,…
Control Co-Design (CCD) integrates physical and control system design to improve the performance of dynamic and autonomous systems. Despite advances in uncertainty-aware CCD methods, real-world uncertainties remain highly unpredictable.…
Early detection of gastric cancer, a leading cause of cancer-related mortality worldwide, remains hampered by the limitations of current diagnostic technologies, leading to high rates of misdiagnosis and missed diagnoses. To address these…
Accurate and robust drug response prediction is of utmost importance in precision medicine. Although many models have been developed to utilize the representations of drugs and cancer cell lines for predicting cancer drug responses (CDR),…
Accurate prediction of tumor trajectories under standard-of-care (SoC) therapies remains a major unmet need in oncology. This capability is essential for optimizing treatment planning and anticipating disease progression. Conventional…
Cardiac digital twins are computational tools capturing key functional and anatomical characteristics of patient hearts for investigating disease phenotypes and predicting responses to therapy. When paired with large-scale computational…
Breast cancer is one of the deadliest cancer worldwide. Timely detection could reduce mortality rates. In the clinical routine, classifying benign and malignant tumors from ultrasound (US) imaging is a crucial but challenging task. An…
An important part of breast cancer staging is the assessment of the sentinel axillary node for early signs of tumor spreading. However, this assessment by pathologists is not always easy and retrospective surveys often requalify the status…
Cervical cancer is the second most prevalent cancer affecting women today. As the early detection of cervical carcinoma relies heavily upon screening and pre-clinical testing, digital cervicography has great potential as a primary or…
Pancreatic ductal adenocarcinoma (PDAC) presents a critical global health challenge, and early detection is crucial for improving the 5-year survival rate. Recent medical imaging and computational algorithm advances offer potential…
In breast cancer, neoadjuvant chemotherapy (NAC) provides a standard treatment option for patients who have locally advanced cancer and some large operable tumors. A patient will have better prognosis when he has achieved a pathological…
Accurate classification of brain tumors from MRI scans is critical for effective treatment planning. This study presents a Hybrid Quantum Convolutional Neural Network (HQCNN) that integrates quantum feature-encoding circuits with depth-wise…
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…