Hypertension among Mississippi Workers by Sociodemographic Characteristics and Occupation, Behavioral Risk Factor Surveillance System by Vincent L. Mendy, Rodolfo Vargas, Oluwabunmi Ogungbe, Lei Zhang

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Assessing machine learning for fair prediction of ADHD in school pupils using a retrospective cohort study of linked education and healthcare data by Johnny Downs, Robert Stewart, Alice Wickersham, Sumithra Velupillai, Lucile Ter-Minassian, Natalia Viani, Lauren Cross

“…Sociodemographic biases were effectively reduced by a fair pre-processing algorithm without loss of accuracy.Conclusions ML approaches using linked routinely collected education and health data offer accurate, low-cost and scalable prediction models of ADHD. …”
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Are women leaders significantly better at controlling the contagion during the COVID-19 pandemic? by Maxwell SALVATORE, Bhramar MUKHERJEE

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Reply to “Vaccination caused underestimation of cumulative incidence of SARS-CoV-2 infection” by Jefferson M. Jones, Melissa M. Coughlin, Eduard Grebe, Michael P. Busch, Kristie E. N. Clarke

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Key technologies and new challenges on body area networks by Xiaolin FANG, Junzhou LUO

“…As the rapid development of sensing,low-power integrated circuit and wireless communication techniques,body area network becomes a new technology to monitor human health,which provides a new solution for information medical treatment.The key technologies of body area network was firstly introduced,including energy consumption,data transmission,security and privacy and human health data processing.Finally,a series of new challenges in body area network systems was proposed.…”
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Risk of Stroke Associated with Temperature and PM2.5: Taiwan Stroke Registry-based Study by Fung-Chang Sung, Hei-Tung Yip, Cheng-Li Lin, Jiann-Shing Jeng, Jiunn-Tay Lee, Yu Sun, Cheng-Yu Wei, Po-Yen Yeh, Kuang-Hsi Chang, Shang-Yu Chien, Kai-Cheng Hsu, TSR team

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Use of Electronic Data and Existing Screening Tools to Identify Clinically Significant Obstructive Sleep Apnea by Carl A Severson, Sachin R Pendharkar, Paul E Ronksley, Willis H Tsai

“…OBJECTIVES: To assess the ability of electronic health data and existing screening tools to identify clinically significant obstructive sleep apnea (OSA), as defined by symptomatic or severe OSA.…”
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Characterizing pediatric discharge diagnoses associated with daily extreme heat exposure in the Midwestern US: A retrospective case-crossover study by Sarah Oerther, Zachary Phillips, Zidong Zhang, Joanne Salas, Sarah Farabi, Tamara Otey

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The epidemiology and clinical presentation of seropositive neuromyelitis optica spectrum disorder in a US population by Aaron M. Carlson, Carlos E.V. Sollero, Andrew B. Wolf, Stefan Sillau, Barrie L. Schmitt, Kelli M. Money, Kavita V. Nair, Amanda L. Piquet, Jeffrey L. Bennett

“…Methods We completed a retrospective observational study of adult patients in the University of Colorado Health System from 1 January 2011 to 31 December 2020, using Health Data Compass (HDC), a data warehouse that combines electronic health information with claims and public health data in Colorado. …”
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Early antibiotics administration reduces mortality in sepsis patients in tertiary care hospital by Suramath Isaranuwatchai, Jirawat Buppanharun, Thamonwan Thongbun, Kaewklao Thavornwattana, Monprach Harnphadungkit, Taweegrit Siripongboonsitti

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Mapping Your World with Community Analyst: An Easy to Use Tool to Map the Characteristics of U.S. Communities by Robert Swett, Lisa Krimsky

“…This article presents Community Analyst, a web application that provides access to thousands of business, demographic, economic, education, and health data variables for the United States. The application’s extensive suite of data metrics, in conjunction with on-demand reports and interactive color-coded maps, allows one to quickly explore the characteristics of one or more geographic areas. …”
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Research progress of human health IoT based on wearable and implantable techniques by Junge LIANG, Yiran SONG, Yangfan SUN, Yingying JI, Lijia PAN, Yi SHI

“…Monitoring various physiological parameters in healthy people daily life can provide early warning of abnormalities and diseases, as well as reduce the pressure on national public health and medical resources.Hence, it is necessary to develop human health IoT system based on wearable and implantable sensors.The bioinformatics detection based on body fluids and electrical signals as the entry point was used to divide sensing technologies, and the key technologies such as self-powered and near-end communication for human health IoT were introduced for discussion.Finally, the technological progress and industrial application in the field of health data management and disease diagnosis and prevention were explored, and the concept of human health IoT based on wearable and implantable technologies was attempted to be constructed.…”
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The effects of PM2.5 air pollution on human health: A narrative review with a focus on cerebrovascular diseases by Leticia Simo

“…This paper synthesizes recent findings from epidemiological studies, mechanistic insights from experimental research, and global health data to elucidate the multifaceted impact of PM2.5 exposure on cerebrovascular health. …”
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Wearable fractal integrated antennas for medical applications by Reha Abdelati, Benkhadda Oumaima, Harrou Meryama, Saih Mohamed

“…Integrated into wearable devices, these antennas facilitate the transmission and reception of crucial health data, such as pulse rate, body temperature, and blood pressure, to healthcare professionals or real-time monitoring systems. …”
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Variability and performance of NHS England’s ‘reason to reside’ criteria in predicting hospital discharge in acute hospitals in England: a retrospective, observational cohort study... by Elizabeth Sapey, Simon Ball, David McNulty, Felicity Evison, Suzy Gallier, Katherine Reeves

“…We aimed to understand the degree of intercentre and intracentre variation in R2R-related metrics reported to NHSE, define an SDM implemented within a single centre Electronic Health Record to generate an electronic R2R (eR2R) and evaluate its performance in predicting subsequent discharge.Design Retrospective observational cohort study using routinely collected health data.Setting 122 NHS Trusts in England for national reporting and an acute hospital in England for local reporting.Participants 6 602 706 patient-days were analysed using 3-month national data and 1 039 592 patient-days, using 3-year single centre data.Main outcome measures Variability in R2R-related metrics reported to NHSE. …”
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Mapping Your World with Community Analyst: An Easy to Use Tool to Map the Characteristics of U.S. Communities by Robert Swett, Lisa Krimsky

“…This article presents Community Analyst, a web application that provides access to thousands of business, demographic, economic, education, and health data variables for the United States. The application’s extensive suite of data metrics, in conjunction with on-demand reports and interactive color-coded maps, allows one to quickly explore the characteristics of one or more geographic areas. …”
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Blood absolute lymphocyte count and trajectory are important in understanding severe COVID-19 by Catharine I. Paules, Jacqueline A. Nordwall, Kathryn Shaw-Saliba, Judith A. Aberg, Edward M. Gardner, Anna L. Goodman, N. Kumarasamy, Shikha Vasudeva, David M. Vock, Crystal M. North, Jens Lundgren, Neil R. Aggarwal, for the STRIVE Network and TICO Trial Study Group

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Generating unseen diseases patient data using ontology enhanced generative adversarial networks by Chang Sun, Michel Dumontier

“…Abstract Generating realistic synthetic health data (e.g., electronic health records), holds promise for fundamental research, AI model development, and enhancing data privacy safeguards. …”
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Interoperable Internet of Medical Things platform for e-Health applications by Jesús Noel Sárez Rubí, Paulo Roberto de Lira Gondim

“…Moreover, the heterogeneity in the large volume of health data generated by Internet of Medical Things platforms must be attenuated for the proper application of big data processing techniques. …”
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Responsible Design, Integration, and Use of Generative AI in Mental Health by Oren Asman, John Torous, Amir Tal

“…It brings together evidence and insights on GenAI’s capabilities, such as emotion recognition, therapy-session summarization, and risk assessment, while highlighting the sensitive nature of mental health data and the need for rigorous validation. Contributors discuss how bias, alignment with human values, transparency, and empathy must be carefully addressed to ensure ethically grounded, artificial intelligence–assisted care. …”
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