Artificial intelligence in drug discovery for fungal diseases: a scoping review [0.03%]
人工智能在真菌疾病药物发现中的应用：系统综述
Henrique Gabriel Wuchryn Martins,Daniela Gorski,Bernardo Mussa et al.
Henrique Gabriel Wuchryn Martins et al.
Background: Fungal diseases represent a global health threat, with high mortality rates and growing antifungal resistance demanding new therapeutic strategies. Artificial intelligence (AI) has emerged as a key methodology...
Duy Le,Tien Nguyen,Huyen Nguyen et al.
Duy Le et al.
Silicosis is a serious occupational lung disease caused by exposure to crystalline silica dust and remains difficult to detect early in at-risk worker populations. In this paper, we introduce the Silicosis Diagnosis Dataset (SDD), which com...
Mitigating bias in chest X-ray disease diagnosis via de-biased disentangled representation learning [0.03%]
通过去偏解耦表征学习减轻胸片疾病诊断中的偏差
Xinwei Lai,Jie Li,Xinbo Gao et al.
Xinwei Lai et al.
Ensuring fairness and reliability in AI-driven healthcare systems is critical, particularly in chest X-ray diagnosis, where models often exhibit subgroup biases. While existing methods primarily address biases from imbalanced data, they ove...
Artificial intelligence in pain assessment and management for older adults: A scoping review [0.03%]
老年人疼痛评估与管理的人工智能应用：综述研究
Rhoda Ilenwabor,Mohammed Mohammed,Nataly Martini
Rhoda Ilenwabor
Introduction: Conventional pain management strategies often fall short in addressing the complex needs of older adults with pain. Artificial intelligence (AI) represents a significant potential for advancing personalized,...
Rustam Zhumagambetov,Niklas Giesa,Sebastian D Boie et al.
Rustam Zhumagambetov et al.
Machine learning (ML) holds great promise to support, improve, and automatize clinical decision-making in hospitals. Model training on abundantly available routine data, however, is hindered by data protection regulations. Generative models...
MediCARE: Medical Collaborative Agents REasoning over Interpretable Heterogeneous Graphs [0.03%]
基于可解释异构图的医疗协作智能体 MediCARE
Antonino Ferraro,Antonio Galli,Valerio La Gatta et al.
Antonino Ferraro et al.
In the era of Artificial Intelligence (AI), Large Language Models (LLMs) are increasingly being used as medical reasoning agents. However, the risk of LLM hallucinations, where the model generates incorrect or nonsensical responses, poses a...
Evidential reasoning-enabled deep learning for reliable treatment outcome prediction in cancer therapy [0.03%]
基于证候的深度学习在癌症治疗中的可靠疗效预测方法研究
Xi Chen,Xiaoxu Deng,Zhiguo Zhou
Xi Chen
Treatment outcome prediction plays an important role in realizing personalized cancer therapy. In triple-negative breast cancer (TNBC), neoadjuvant chemotherapy (NAC) is widely used to downstage tumors and improve surgical outcomes. In head...
EPPCMinerBen: A novel benchmark for evaluating large language models on electronic patient-provider communication via the patient portal [0.03%]
EPPCMinerBen：一个用于评估大型语言模型通过患者门户进行电子病患沟通的新基准
Samah Jamal Fodeh,Yan Wang,Linhai Ma et al.
Samah Jamal Fodeh et al.
Effective communication in health care is critical for treatment outcomes and adherence. With patient-provider exchanges shifting to secure messaging, analyzing electronic patient-communication (EPPC) data is both essential and challenging....
DARE: A Deformable Adaptive Regularization Estimator for learning-based medical image registration [0.03%]
一种基于学习的医学图像配准的可变形自适应正则化方法(DARE)
Ahsan Raza Siyal,Markus Haltmeier,Ruth Steiger et al.
Ahsan Raza Siyal et al.
Deformable medical image registration is a fundamental task in medical image analysis. While deep learning-based methods have demonstrated superior accuracy and efficiency, they often overlook the critical role of regularization in ensuring...
Artificial intelligence language models for medical text analysis: A systematic review [0.03%]
医学文本分析的人工智能语言模型系统综述
Amir Sorayaie Azar,Jamshid Bagherzadeh Mohasefi,Uffe Kock Wiil et al.
Amir Sorayaie Azar et al.
Medical text records serve as essential repositories of patient information, providing a foundation for informed clinical decision-making, accurate diagnosis, reliable prognosis, and effective treatment planning. Recent advancements in Arti...