Related papers: DC3 -- A Diagnostic Case Challenge Collection for …
Disease progression models are widely used to inform the diagnosis and treatment of many progressive diseases. However, a significant limitation of existing models is that they do not account for health disparities that can bias the…
Arrhythmias are irregularities in the hearts electrical system which cause rapid and irregular heartbeats. These heart conditions affect over 33 million people globally and significantly increase the risk of severe complications, including…
Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. In this paper, we present a natural language processing approach based on deep learning to automatically identify clinically…
Medical document analysis plays a crucial role in extracting essential clinical insights from unstructured healthcare records, supporting critical tasks such as differential diagnosis. Determining the most probable condition among…
This research focuses on evaluating and enhancing data readiness for the development of an Artificial Intelligence (AI)-based Clinical Decision Support System (CDSS) in the context of skin cancer treatment. The study, conducted at the Skin…
This article presents the results of the research carried out on the development of a medical diagnostic system applied to the Acute Bacterial Meningitis, using the Case Based Reasoning methodology. The research was focused on the…
Healthcare professionals need effective ways to use, understand, and validate AI-driven clinical decision support systems. Existing systems face two key limitations: complex visualizations and a lack of grounding in scientific evidence. We…
A key step in medical diagnosis is giving the patient a universally recognized label (e.g. Appendicitis) which essentially assigns the patient to a class(es) of patients with similar body failures. However, two patients having the same…
Dialogue systems for mental health care aim to provide appropriate support to individuals experiencing mental distress. While extensive research has been conducted to deliver adequate emotional support, existing studies cannot identify…
Today's AI systems for medical decision support often succeed on benchmark datasets in research papers but fail in real-world deployment. This work focuses on the decision making of sepsis, an acute life-threatening systematic infection…
We introduce Baichuan-M3, a medical-enhanced large language model engineered to shift the paradigm from passive question-answering to active, clinical-grade decision support. Addressing the limitations of existing systems in open-ended…
Critical appraisal of scientific literature is an essential skill in the biomedical field. While large language models (LLMs) can offer promising support in this task, their reliability remains limited, particularly for critical reasoning…
Machine Learning (ML) is used to tackle various tasks, such as disease classification and prediction. The effectiveness of ML models relies heavily on having large amounts of complete data. However, healthcare data is often limited or…
Medical imaging is an important research field with many opportunities for improving patients' health. However, there are a number of challenges that are slowing down the progress of the field as a whole, such optimizing for publication. In…
Clinical decision support systems have been developed to help physicians to take clinical guidelines into account during consultations. The ASTI critiquing module is one such systems; it provides the physician with automatic criticisms when…
Each year there are nearly 57 million deaths around the world, with over 2.7 million in the United States. Timely, accurate and complete death reporting is critical in public health, as institutions and government agencies rely on death…
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.…
Skin conditions affect an estimated 1.9 billion people worldwide. A shortage of dermatologists causes long wait times and leads patients to seek dermatologic care from general practitioners. However, the diagnostic accuracy of general…
Diagnostic processes for complex cyber-physical systems often require extensive prior knowledge in the form of detailed system models or comprehensive training data. However, obtaining such information poses a significant challenge. To…
Decision support systems based on prediction sets help humans solve multiclass classification tasks by narrowing down the set of potential label values to a subset of them, namely a prediction set, and asking them to always predict label…