Machine learning-based early detection of tuberculosis in asymptomatic high-risk populations [0.03%]
基于机器学习的无症状高危人群结核病早期检测
Hrushikesh Jaiwant Joshi,Minal Barhate,Kiran Prabhakar More et al.
Hrushikesh Jaiwant Joshi et al.
Tuberculosis (TB) remains a major global health challenge and continues to affect millions worldwide despite decades of control efforts. The disease can remain dormant and symptom-free for long periods, especially in high-risk populations s...
Deep learning for automated sputum smear microscopy in tuberculosis diagnosis [0.03%]
结核病诊断环境下涂片镜检的深度学习技术
Chandrakant Kokane,Neeta A Deshpande,Harsha Avinash Bhute et al.
Chandrakant Kokane et al.
Background: Tuberculosis (TB) is one of the world's major health issues, especially in low- and middle-income nations without many diagnostic methods. TB is a widespread global disease that continues to be a problem of lo...
Federated learning framework for predicting multi-drug resistant tuberculosis across regional databases [0.03%]
跨区域数据库预测耐多药结核病的联邦学习框架
Harsha Avinash Bhute,Avinash N Bhute,Kishor B Waghulde et al.
Harsha Avinash Bhute et al.
Background: Multi-Drug Resistant Tuberculosis (MDR-TB) is a major public health problem around the world, especially in low- and middle-income countries where quick and accurate testing is needed for effective treatment a...
AI-driven drug resistance profiling in tuberculosis patients: A transfer learning approach [0.03%]
基于人工智能的结核病患者的药物耐药性分析：迁移学习方法
Prashant Wakhare,Shagufta Md S Sheikh,Pragati Mahale et al.
Prashant Wakhare et al.
Background: Tuberculosis (TB) is still the most common infectious disease that kills people around the world. Drug-resistant types like multi-drug resistant (MDR-TB) and widely drug-resistant TB (XDR-TB) are becoming more...
Deep learning on genomic sequences for rapid identification of drug-resistant tuberculosis [0.03%]
深度学习在基因组序列上的应用促进快速识别耐药结核病
Sunil Bajeja,Kandula Jayapaul,Poonam Gaur et al.
Sunil Bajeja et al.
Background: The bacteria Mycobacterium tuberculosis (MTB) cause tuberculosis (TB), which is still a major public health problem around the world. This is especially true now that drug-resistant forms of TB like Multi-Drug...
Reinforcement learning to optimize tuberculosis screening strategies in resource-limited settings [0.03%]
利用强化学习优化资源匮乏地区的结核病筛查策略
Prakash Nandkumar Kalavadekar,Kiran Ramesh Khandarkar,Dhanraj R Dhotre et al.
Prakash Nandkumar Kalavadekar et al.
Still, tuberculosis (TB) is a big health problem all over the world. It is very hard to find cases quickly in places that don't have many resources or fair access to care. Screening methods from the past, such as x-rays, symptom-based asses...
Harnessing semi-supervised graph-based learning to advance automated bacilli detection in digital tuberculosis microscopy with limited expert annotations [0.03%]
利用半监督图学习方法在专家标注数据稀缺的情况下推进结核病数字显微镜下的分枝杆菌自动化检测技术
Pragati Pandit,Sanjay Thorat,Shilpy Singh et al.
Pragati Pandit et al.
Automated acid-fast bacilli (AFB) detection with digital microscopy is important for the improvement of tuberculosis diagnosis in communities or populations where expert annotations are not available. In this paper, we propose a semi-superv...
Hierarchical taxonomy-aware modeling for granular drug resistance and disease outcome prediction in multimodal tuberculosis cohorts [0.03%]
面向多模态结核病队列的分层层级分类意识建模以进行细化药物抗性及疾病结果预测
Jambi Ratna Raja Kumar,Laxmi Bewoor,Kalyani Kadam et al.
Jambi Ratna Raja Kumar et al.
Tuberculosis is a disease with many phenotypes, complicated by the hierarchical clinical taxonomies of drug resistance that are not typically leveraged in existing predictive modeling. We developed a taxonomy-driven, hierarchical classifica...
Enabling real-time tuberculosis detection in hospital radiology through scalable actor-learner architectures for distributed deep reinforcement learning [0.03%]
基于分布式深度强化学习的可扩展演员-学员架构在医院放射科实现实时检测肺结核
Poonam Chaudhary,Shweta Bandhekar,Padmakant Umakant Dhage et al.
Poonam Chaudhary et al.
The increasing demand for timely tuberculosis detection in hospital radiology necessitates scalable and efficient automated screening solutions. This study presents a novel application of the IMPALA distributed deep reinforcement learning a...
Cross-domain generative translation of cough audio biomarkers for tuberculosis screening across diverse global populations [0.03%]
跨域生成性翻译咳嗽生物标志物音频表征以筛查全球各地的人群中的结核病
Mukul Pande,Aparna Patange,Sameer Rastogi et al.
Mukul Pande et al.
Accurate and equitable tuberculosis (TB) screening using cough audio biomarkers is challenged by domain shifts arising from heterogeneous recording environments, devices, and subject demographics. This study addresses these challenges by le...