Clustering Breast Cancer Patients Based on Their Treatment Courses Using German Cancer Registry Data [0.03%]
基于德国癌症登记数据的乳腺癌患者治疗过程聚类分析
Kolja Blohm,David Korfkamp,Florian Oesterling et al.
Kolja Blohm et al.
Cancer registries collect extensive data on cancer patients, including diagnoses, treatments, and disease progression. These data offer valuable insights into cancer care, but it is challenging to analyze due to its complexity. Machine lear...
Leveraging EHR Data and Up-to-Date Clinical Guidelines for Highly Accurate and Practical Clinical Diabetes Drug and Dosage Recommendation System [0.03%]
基于电子健康档案数据和最新临床指南的高准确性和实用性的临床糖尿病药物剂量推荐系统
Jhing-Fa Wang,Ming-Jun Wei,Tzu-Chun Yeh et al.
Jhing-Fa Wang et al.
Background: Existing drug recommendation systems lack integration with up-to-date clinical guidelines (the latest diabetes association standards of care and clinical guidelines that align with local government healthcare ...
Alternative Strategies to Generate Class Activation Maps Supporting AI-based Advice in Vertebral Fracture Detection in X-ray Images [0.03%]
支持基于AI建议的X射线图像脊椎骨折检测的替代类激活图生成策略
Samuele Pe,Lorenzo Famiglini,Enrico Gallazzi et al.
Samuele Pe et al.
Balancing artificial intelligence (AI) support with appropriate human oversight is challenging, with associated risks such as algorithm aversion and technology dominance. Research areas like eXplainable AI (XAI) and Frictional AI aim to add...
Unlocking the Potential of the Next Generation: Methods of Information in Medicine Student Paper Award 2024 [0.03%]
释放下一代的潜力：2024年医学学生论文奖信息方法奖项
Sabine Koch,John H Holmes,Lucia Sacchi
Sabine Koch
TCMSF: A construction framework of traditional Chinese medicine syndrome ancient book knowledge graph [0.03%]
TCMSF：传统中医药症古籍知识图谱的构建框架
Ziling Zeng,Lin Tong,Bing Li et al.
Ziling Zeng et al.
Background: Syndrome is a unique and crucial concept in traditional Chinese medicine (TCM). However, much of the syndrome knowledge lacks systematic organization and correlation, and current information technologies are u...
Automated Information Extraction from Unstructured Hematopathology Reports to Support Response Assessment in Myeloproliferative Neoplasms [0.03%]
自动从不结构化的血液病理报告中提取信息以支持骨髓增生性肿瘤的应答评估
Spencer Krichevsky,Evan T Sholle,Prakash Adekkanattu et al.
Spencer Krichevsky et al.
Background: Assessing treatment response in patients with myeloproliferative neoplasms is difficult because data components exist in unstructured bone marrow pathology (hematopathology) reports, which require specialized,...
Large-Scale Integration of DICOM Metadata into HL7-FHIR for Medical Research [0.03%]
大规模集成DICOM元数据到HL7-FHIR以支持医学研究
Alexa Iancu,Johannes Bauer,Matthias S May et al.
Alexa Iancu et al.
Background: The current gap between the availability of routine imaging data and its provisioning for medical research hinders the utilization of radiological information for secondary purposes. To address this, the Germ...
Response to Commentary by Dehaene et al. on Synthetic Discovery is not only a Problem of Differentially Private Synthetic Data [0.03%]
对Dehaene等人关于合成发现的评论的答复：差分隐私合成数据不仅仅是问题所在
Ileana Montoya Perez,Parisa Movahedi,Valtteri Nieminen et al.
Ileana Montoya Perez et al.
Why Synthetic Discoveries are Not Only a Problem of Differentially Private Synthetic Data [0.03%]
合成发现不仅仅是差分隐私合成数据的问题的原因探究
Heidelinde Dehaene,Alexander Decruyenaere,Christiaan Polet et al.
Heidelinde Dehaene et al.
Päivi Nurmela,Minna Marjetta Mykkänen,Ulla-Mari Kinnunen
Päivi Nurmela
Background In the operating theatre, a large collection of data is collected at each visit. Some of this data is patient information, some is related to resource management, which is linked to hospital finances. Poor quality data leads to p...