A mixed methods evaluation of a pilot open trial of a mentor-guided digital intervention for youth anxiety [0.03%]
青年人焦虑障碍辅导导师数字化干预试点开放试验的混合方法评估
Emma C Wolfe,Alexandra Werntz,Audrey Michel et al.
Emma C Wolfe et al.
Digital mental health interventions (DMHIs), such as cognitive bias modification for interpretations (CBM-I), offer promise for increasing access to anxiety treatment among underserved adolescents, but data regarding their efficacy are mixe...
SomaVR: A low-cost virtual reality platform and implementation framework for medical education in resource-limited settings [0.03%]
SomaVR：一种低成本虚拟现实平台和实施框架，用于资源匮乏环境下的医学教育
Mike Nsubuga,Grace Kebirungi,Helen Please et al.
Mike Nsubuga et al.
Quality medical training is vital for effective healthcare worldwide. In low- and middle-income countries (LMICs), traditional training methods often face significant challenges, including limited resources, logistical barriers, and difficu...
Classification of knowledge of fertility period among adolescent girls in East Africa from 2012 to 2022: Machine learning algorithm [0.03%]
东非地区2012至2022年少女对排卵期认知的分类研究——机器学习算法
Andualem Addisu Birlie,Kassahun Dessie Gashu,Mulugeta Desalegn Kasaye et al.
Andualem Addisu Birlie et al.
Understanding the time of the menstrual cycle would help women to avoid getting pregnant without the need for surgical, hormonal, or mechanical contraception. Women who do not use contraception and do not know when they are fertile are at a...
Trialling the efficacy of a technological visuo-cognitive training program as a compensatory tool for visual rehabilitation after stroke: A pilot study [0.03%]
卒中后视觉康复的高科技视觉认知训练项目的有效性的试点研究
Lewis Jefferson,Abbey Fletcher,Beckie Morris et al.
Lewis Jefferson et al.
Visual impairments are common post-stroke and can lead to diminished functioning and difficulty accomplishing everyday tasks, such as reading and navigating unfamiliar environments independently. This pilot study investigates the usability,...
First-line risk stratification with machine learning models facilitates rapid triage for non-ST-elevation myocardial infarction [0.03%]
基于机器学习的风险分层模型可促进非ST段抬高性心肌梗死的快速分类评估
Wei-Jia Luo,Yih-Mei Liou,Cheng-Han Hsiao et al.
Wei-Jia Luo et al.
Timely diagnosis of non-ST-elevation myocardial infarction (NSTEMI) remains challenging, as current protocols rely on serial high-sensitivity cardiac troponin (hs-cTn) tests that may delay decisions and overcrowd emergency departments. We r...
AID-FGS: Artificial intelligence-enabled diagnosis of female genital schistosomiasis: Preliminary findings [0.03%]
基于人工智能的女性生殖器血吸虫病诊断:AID-FGS初步研究发现
Akanksha Sharma,Tanmoy Dam,Sepo Mwangelwa et al.
Akanksha Sharma et al.
Female genital schistosomiasis (FGS) is a sequela of infection with a waterborne parasite prevalent in sub-Saharan Africa and is associated with increased HIV risk. Diagnosis of FGS involves visual colposcopic identification of lesions on t...
Fine-tuning foundational models to code diagnoses from veterinary health records [0.03%]
从兽医健康记录中对代码诊断进行基础模型的微调
Mayla R Boguslav,Adam Kiehl,David Kott et al.
Mayla R Boguslav et al.
Veterinary medical records represent a large data resource for application to veterinary and One Health clinical research efforts. Use of the data is limited by interoperability challenges including inconsistent data formats and data siloin...
Topologically distinct 2D and 3D intratumoral heterogeneity scores for preoperatively predicting invasiveness in stage I lung adenocarcinoma: A multicenter study [0.03%]
基于多中心研究的I期肺腺癌侵袭性的术前预测：拓扑学不同的二维和三维瘤内异质性评分
Zhichao Zuo,Xiaohong Fan,Ying Zeng et al.
Zhichao Zuo et al.
This multicenter study aims to enhance the preoperative prediction of pathological invasiveness in clinical stage I lung adenocarcinoma (LUAD) by developing and validating topologically distinct 2D and 3D intratumoral heterogeneity (ITH) sc...
Machine learning based classification of aggressive and malignant renal tumors from multimodal data [0.03%]
基于机器学习的多模态数据肾癌分类
Mehrnegar Aminy,Tejal Gala,Agnimitra Dasgupta et al.
Mehrnegar Aminy et al.
This study aimed to develop and evaluate a machine learning pipeline using multiphase contrast-enhanced CT images and clinical data to classify renal tumors as benign, malignant-indolent, or malignant-aggressive, while assessing the contrib...
Bridging the divide in digital therapeutics (DTx): Partnership strategies for broader representation across DTx development and deployment [0.03%]
弥合数字疗法(DTx)领域差距的战略：扩大DTx开发和部署中的多方合作与参与
Meelim Kim,Steven De La Torre,Uchechi Mitchell et al.
Meelim Kim et al.
While Digital Therapeutics (DTx) are widely considered a key strategy to reach certain populations with unmet healthcare needs, a range of differences in the impact and adoption of DTx still exists. These differences are not just rooted in ...