日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

A machine learning model for prediction of early-onset neonatal sepsis in low-income and middle-income countries: development and validation study

用于预测低收入和中等收入国家新生儿早期败血症的机器学习模型:开发和验证研究

Kainth, Deepika; Gupta, Ayushi; Singh, Pradeep; Prakash, Satya; Thukral, Anu; Deorari, Ashok; Kapoor, Mudit; Agarwal, Ramesh; Sethi, Tavpritesh; Sankar, M Jeeva

Clinico-genomic study reveals association of dengue virus genome high frequency mutations with dengue disease severity

临床基因组学研究揭示登革病毒基因组高频突变与登革热疾病严重程度相关

Ravi, Varsha; Imran, Md; Khare, Kriti; Mishra, Pallavi; Mohite, Ramakant; Kanika; Khan, Md Abuzar; Swaminathan, Aparna; Yadav, Aanchal; Sinha, Sristi; Shukla, Richa; Chattopadhyay, Partha; Soni, Jyoti; Maurya, Ranjeet; Sethi, Tavpritesh; Tarai, Bansidhar; Budhiraja, Sandeep; Pandey, Rajesh

Genomic hotspots in the DENV-2 serotype (E, NS4B, and NS5 genes) are associated with dengue disease severity in the endemic region of India

在印度的登革热流行区,DENV-2血清型(E、NS4B和NS5基因)的基因组热点与登革热疾病的严重程度相关。

Ravi, Varsha; Khare, Kriti; Mohite, Ramakant; Mishra, Pallavi; Halder, Sayanti; Shukla, Richa; Liu, Chinky Shiu Chen; Yadav, Aanchal; Soni, Jyoti; Chaudhary, Komal; Tarai, Bansidhar; Budhiraja, Sandeep; Khosla, Pooja; Sethi, Tavpritesh; Imran, Md; Pandey, Rajesh

Mining Trends of COVID-19 Vaccine Beliefs on Twitter With Lexical Embeddings: Longitudinal Observational Study

利用词汇嵌入挖掘推特上关于新冠疫苗信念的趋势:一项纵向观察研究

Chopra, Harshita; Vashishtha, Aniket; Pal, Ridam; Tyagi, Ananya; Sethi, Tavpritesh

A call for citizen science in pandemic preparedness and response: beyond data collection

呼吁公民科学参与疫情防范和应对:超越数据收集

Tan, Yi-Roe; Agrawal, Anurag; Matsoso, Malebona Precious; Katz, Rebecca; Davis, Sara L M; Winkler, Andrea Sylvia; Huber, Annalena; Joshi, Ashish; El-Mohandes, Ayman; Mellado, Bruce; Mubaira, Caroline Antonia; Canlas, Felipe C; Asiki, Gershim; Khosa, Harjyot; Lazarus, Jeffrey Victor; Choisy, Marc; Recamonde-Mendoza, Mariana; Keiser, Olivia; Okwen, Patrick; English, Rene; Stinckwich, Serge; Kiwuwa-Muyingo, Sylvia; Kutadza, Tariro; Sethi, Tavpritesh; Mathaha, Thuso; Nguyen, Vinh Kim; Gill, Amandeep; Yap, Peiling

Predicting Emerging Themes in Rapidly Expanding COVID-19 Literature With Unsupervised Word Embeddings and Machine Learning: Evidence-Based Study

利用无监督词嵌入和机器学习预测快速增长的 COVID-19 文献中的新兴主题:一项基于证据的研究

Pal, Ridam; Chopra, Harshita; Awasthi, Raghav; Bandhey, Harsh; Nagori, Aditya; Sethi, Tavpritesh

Single-cell multiomics revealed the dynamics of antigen presentation, immune response and T cell activation in the COVID-19 positive and recovered individuals

单细胞多组学揭示了 COVID-19 阳性和康复个体中抗原呈递、免疫反应和 T 细胞活化的动态

Partha Chattopadhyay, Kriti Khare, Manish Kumar, Pallavi Mishra, Alok Anand, Ranjeet Maurya, Rohit Gupta, Shweta Sahni, Ayushi Gupta, Saruchi Wadhwa, Aanchal Yadav, Priti Devi, Kishore Tardalkar, Meghnad Joshi, Tavpritesh Sethi, Rajesh Pandey

Early prediction of hypothermia in pediatric intensive care units using machine learning

利用机器学习对儿科重症监护病房中的低体温进行早期预测

Singh, Pradeep; Nagori, Aditya; Lodha, Rakesh; Sethi, Tavpritesh

Early Prediction of Hemodynamic Shock in Pediatric Intensive Care Units With Deep Learning on Thermal Videos

利用深度学习和热成像视频对儿科重症监护病房中的血流动力学休克进行早期预测

Vats, Vanshika; Nagori, Aditya; Singh, Pradeep; Dutt, Raman; Bandhey, Harsh; Wason, Mahika; Lodha, Rakesh; Sethi, Tavpritesh

Genomic Surveillance of COVID-19 Variants With Language Models and Machine Learning

利用语言模型和机器学习进行 COVID-19 变异株的基因组监测

Nagpal, Sargun; Pal, Ridam; Ashima; Tyagi, Ananya; Tripathi, Sadhana; Nagori, Aditya; Ahmad, Saad; Mishra, Hara Prasad; Malhotra, Rishabh; Kutum, Rintu; Sethi, Tavpritesh