Investigating Associations Between Prognostic Factors in Gliomas: Unsupervised Multiple Correspondence Analysis [0.03%]
胶质瘤预后因素之间关联的探究：无监督多重对应分析
Maria Eduarda Goes Job,Heidge Fukumasu,Tathiane Maistro Malta et al.
Maria Eduarda Goes Job et al.
Background: Multiple correspondence analysis (MCA) is an unsupervised data science methodology that aims to identify and represent associations between categorical variables. Gliomas are an aggressive type of cancer chara...
Extracting Knowledge From Scientific Texts on Patient-Derived Cancer Models Using Large Language Models: Algorithm Development and Validation Study [0.03%]
基于患者衍生癌症模型的科学文本知识提取：大型语言模型算法开发与验证研究
Jiarui Yao,Zinaida Perova,Tushar Mandloi et al.
Jiarui Yao et al.
Background: Patient-derived cancer models (PDCMs) have become essential tools in cancer research and preclinical studies. Consequently, the number of publications on PDCMs has increased significantly over the past decade....
Using Natural Language Processing to Identify Symptomatic Adverse Events in Pediatric Oncology: Tutorial for Clinician Researchers [0.03%]
基于自然语言处理的儿童肿瘤学症状型不良事件识别：临床研究人员教程
Clifton P Thornton,Maryam Daniali,Lei Wang et al.
Clifton P Thornton et al.
Artificial intelligence (AI) is poised to become an integral component in health care research and delivery, promising to address complex challenges with unprecedented efficiency and precision. However, many clinicians lack training and exp...
A Framework for Race-Specific Prostate Cancer Detection Using Machine Learning Through Gene Expression Data: Feature Selection Optimization Approach [0.03%]
基于基因表达数据利用机器学习进行前列腺癌种族特异性检测的框架：特征选择优化方法
David Agustriawan,Adithama Mulia,Marlinda Vasty Overbeek et al.
David Agustriawan et al.
Background: Previous machine learning approaches for prostate cancer detection using gene expression data have shown remarkable classification accuracies. However, prior studies overlook the influence of racial diversity ...
Decentralized Biobanking Apps for Patient Tracking of Biospecimen Research: Real-World Usability and Feasibility Study [0.03%]
分散式生物样本库应用程序用于患者生物样本研究的生物样本追踪：真实世界使用性和可行性研究
William Sanchez,Ananya Dewan,Eve Budd et al.
William Sanchez et al.
Background: Biobank privacy policies strip patient identifiers from donated specimens, undermining transparency, utility, and value for patients, scientists, and society. We are advancing decentralized biobanking apps tha...
A Hybrid Deep Learning-Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Survivors of Cancer: Cross-Sectional Study [0.03%]
用于支持癌症幸存者长期行为结果早期检测的基于混合深度学习的功能选择方法：横断面研究
Tracy Huang,Chun-Kit Ngan,Yin Ting Cheung et al.
Tracy Huang et al.
Background: The number of survivors of cancer is growing, and they often experience negative long-term behavioral outcomes due to cancer treatments. There is a need for better computational methods to handle and predict t...
Effect of a Web-Based Heartfulness Program on the Mental Well-Being, Biomarkers, and Gene Expression Profile of Health Care Students: Randomized Controlled Trial [0.03%]
一种基于网络的心灵呵护计划对医学生心理健康、生物标志物和基因表达的影响：随机对照试验
Jayaram Thimmapuram,Kamlesh D Patel,Deepti Bhatt et al.
Jayaram Thimmapuram et al.
Background: Health care students often experience high levels of stress, anxiety, and mental health issues, making it crucial to address these challenges. Variations in stress levels may be associated with changes in dehy...
Eco-Evolutionary Drivers of Vibrio parahaemolyticus Sequence Type 3 Expansion: Retrospective Machine Learning Approach [0.03%]
致病菌Vibrio parahaemolyticus基因型扩张的生态进化驱动因素：基于机器学习的方法研究回顾
Amy Marie Campbell,Chris Hauton,Ronny van Aerle et al.
Amy Marie Campbell et al.
Background: Environmentally sensitive pathogens exhibit ecological and evolutionary responses to climate change that result in the emergence and global expansion of well-adapted variants. It is imperative to understand th...
Exploring the Intersection of Schizophrenia, Machine Learning, and Genomics: Scoping Review [0.03%]
精神分裂症、机器学习和基因组学的交集：循证综述研究
Alexandre Hudon,Mélissa Beaudoin,Kingsada Phraxayavong et al.
Alexandre Hudon et al.
Background: An increasing body of literature highlights the integration of machine learning with genomic data in psychiatry, particularly for complex mental health disorders such as schizophrenia. These advanced technique...
Enhancing Suicide Risk Prediction With Polygenic Scores in Psychiatric Emergency Settings: Prospective Study [0.03%]
基于精神病急诊环境的心理遗传分数自杀风险预测研究
Younga Heather Lee,Yingzhe Zhang,Chris J Kennedy et al.
Younga Heather Lee et al.
Background: Despite growing interest in the clinical translation of polygenic risk scores (PRSs), it remains uncertain to what extent genomic information can enhance the prediction of psychiatric outcomes beyond the data ...