AI in Global Health: The View from the Front Lines
暂无分享,去创建一个
[1] J. Fanning. The Age of Surveillance Capitalism. The Fight for a Human Future at the New Frontier of Power by Shoshana Zuboff (review) , 2022 .
[2] Donna Harawy. Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective , 2022, Philosophical Literary Journal Logos.
[3] Mikael Wiberg,et al. AI activism , 2021, Interactions.
[4] Anna Lauren Hoffmann,et al. Terms of inclusion: Data, discourse, violence , 2020, New Media Soc..
[5] Bidisha Chaudhuri. Distant, opaque and seamful: seeing the state through the workings of Aadhaar in India , 2021, Inf. Technol. Dev..
[6] Natalia Kovalyova,et al. Data feminism , 2020, Information, Communication & Society.
[7] Syed Attique Shah,et al. A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic , 2020, Chaos, Solitons & Fractals.
[8] Unintended by Design: On the Political Uses of “Unintended Consequences” , 2020 .
[9] Shakir Mohamed,et al. Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence , 2020, Philosophy & Technology.
[10] Raghavendra Selvan,et al. Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models , 2020, ArXiv.
[11] R. Roy. The next billion users: Digital life beyond the West , 2020 .
[12] Benedetta Brevini,et al. Black boxes, not green: Mythologizing artificial intelligence and omitting the environment , 2020, Big Data Soc..
[13] Pratyusha Kalluri. Don’t ask if artificial intelligence is good or fair, ask how it shifts power , 2020, Nature.
[14] Samuel Lalmuanawma,et al. Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review , 2020, Chaos, Solitons & Fractals.
[15] Pushpendra Singh,et al. Exploring Automated Q&A Support System for Maternal and Child Health in Rural India , 2020, COMPASS.
[16] Nimmi Rangaswamy,et al. Good Digital Identity: The Case of Aadhaar in India , 2020, COMPASS.
[17] Milind Tambe,et al. Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement , 2020, ArXiv.
[18] E. Guney,et al. Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare. , 2020, NPJ digital medicine.
[19] R. Fleet,et al. Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries , 2020, Globalization and Health.
[20] E. Guney,et al. Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare , 2020, npj Digital Medicine.
[21] L. Bowleg,et al. We're Not All in This Together: On COVID-19, Intersectionality, and Structural Inequality. , 2020, American journal of public health.
[22] Eric Dagiral,et al. Governance and Accountable Citizenship Through Identification Infrastructures: Database Politics of Copernicus (France) and National Register of Citizens (India) , 2020, Science, Technology and Society.
[23] Mozhgan Seif,et al. Exponentially Increasing Trend of Infected Patients with COVID-19 in Iran: A Comparison of Neural Network and ARIMA Forecasting Models , 2020, Iranian journal of public health.
[24] Dani Kiyasseh,et al. PlethAugment: GAN-Based PPG Augmentation for Medical Diagnosis in Low-Resource Settings , 2020, IEEE Journal of Biomedical and Health Informatics.
[25] Sushil Kumar,et al. Outbreak Trends of Coronavirus Disease–2019 in India: A Prediction , 2020, Disaster Medicine and Public Health Preparedness.
[26] Lauren Wilcox,et al. A Human-Centered Evaluation of a Deep Learning System Deployed in Clinics for the Detection of Diabetic Retinopathy , 2020, CHI.
[27] Munmun De Choudhury,et al. "Like Shock Absorbers": Understanding the Human Infrastructures of Technology-Mediated Mental Health Support , 2020, CHI.
[28] Hanna M. Wallach,et al. Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI , 2020, CHI.
[29] M. Javaid,et al. Artificial Intelligence (AI) applications for COVID-19 pandemic , 2020, Diabetes & Metabolic Syndrome: Clinical Research & Reviews.
[30] Paolo Massimo Buscema,et al. Analysis of the Ebola Outbreak in 2014 and 2018 in West Africa and Congo by Using Artificial Adaptive Systems , 2020, Appl. Artif. Intell..
[31] Andre Dekker,et al. Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics , 2020, Artif. Intell. Medicine.
[32] K. Schulman,et al. Covid-19 and Health Care's Digital Revolution. , 2020, The New England journal of medicine.
[33] Lawrence Carin,et al. Digital technology and COVID-19 , 2020, Nature Medicine.
[34] S. Sindhu,et al. An AI Based Chat-Bot for Providing Health Services , 2020 .
[35] Muthoni Masinde. Africa's Malaria Epidemic Predictor: Application of Machine Learning on Malaria Incidence and Climate Data , 2020, ICCDA.
[36] W. Liang,et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions , 2020, Journal of thoracic disease.
[37] Becky McCall,et al. COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread , 2020, The Lancet Digital Health.
[38] Amba Kak,et al. "The Global South is everywhere, but also always somewhere": National Policy Narratives and AI Justice , 2020, AIES.
[39] S. Merz. Race after technology. Abolitionist tools for the new Jim Code , 2020, Ethnic and Racial Studies.
[40] Assef Jafar,et al. A comparative study on predicting influenza outbreaks using different feature spaces: application of influenza-like illness data from Early Warning Alert and Response System in Syria , 2020, BMC Research Notes.
[41] Marzyeh Ghassemi,et al. Treating health disparities with artificial intelligence , 2020, Nature Medicine.
[42] Federica Lucivero,et al. Big Data, Big Waste? A Reflection on the Environmental Sustainability of Big Data Initiatives , 2019, Science and Engineering Ethics.
[43] J. Kleinberg,et al. Roles for computing in social change , 2019, FAT*.
[44] Isaac Holeman,et al. Human-centered design for global health equity , 2019, Inf. Technol. Dev..
[45] Max Tegmark,et al. The role of artificial intelligence in achieving the Sustainable Development Goals , 2019, Nature Communications.
[46] F. Demaria,et al. The Post-Development Dictionary agenda: paths to the pluriverse , 2017, The Development Dictionary @25.
[47] C. Mohanty,et al. FEMINISM WITHOUT BORDERS , 2011 .
[48] N. M. Ghazaly,et al. Novel coronavirus forecasting model using nonlinear autoregressive artificial neural network , 2020 .
[49] Thiago Antonini Alves,et al. Ensemble method based on Artificial Neural Networks to estimate air pollution health risks , 2020, Environ. Model. Softw..
[50] O. Winther,et al. Systematic review of machine learning for diagnosis and prognosis in dermatology , 2019, The Journal of dermatological treatment.
[51] Lauren E. Salminen,et al. Machine learning classification of neurocognitive performance in children with perinatal HIV initiating de novo antiretroviral therapy. , 2019, AIDS.
[52] S. Fong,et al. Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges. , 2019, Cancer letters.
[53] Ruhul Amin,et al. Disha: An Implementation of Machine Learning Based Bangla Healthcare Chatbot , 2019, 2019 22nd International Conference on Computer and Information Technology (ICCIT).
[54] Charru Malhotra,et al. Designing National Health Stack for Public Health: Role of ICT-Based Knowledge Management System , 2019, 2019 ITU Kaleidoscope: ICT for Health: Networks, Standards and Innovation (ITU K).
[55] N. Muhajarine,et al. Evidence of health inequity in child survival: spatial and Bayesian network analyses of stillbirth rates in 194 countries , 2019, Scientific Reports.
[56] C. Cao,et al. Mapping Environmental Suitability of Scrub Typhus in Nepal Using MaxEnt and Random Forest Models , 2019, International journal of environmental research and public health.
[57] S. Merz. Surrogate humanity: race, robots, and the politics of technological futures , 2019, Ethnic and Racial Studies.
[58] Ahmed Hosny,et al. Artificial intelligence for global health , 2019, Science.
[59] Sean A. Munson,et al. Social Technologies for Digital Wellbeing Among Marginalized Communities , 2019, CSCW Companion.
[60] Walter S. Lasecki,et al. Identifying Challenges and Opportunities in Human-AI Collaboration in Healthcare , 2019, CSCW Companion.
[61] Pushpendra Singh,et al. Engagement of Pregnant Women and Mothers over WhatsApp: Challenges and Opportunities Involved , 2019, CSCW Companion.
[62] Deepika Yadav,et al. Feedpal: Understanding Opportunities for Chatbots in Breastfeeding Education of Women in India , 2019, Proc. ACM Hum. Comput. Interact..
[63] Deepika Yadav,et al. LEAP: Scaffolding Collaborative Learning of Community Health Workers in India , 2019, Proc. ACM Hum. Comput. Interact..
[64] Naveena Karusala,et al. Engaging Feminist Solidarity for Comparative Research, Design, and Practice , 2019, Proc. ACM Hum. Comput. Interact..
[65] Naveena Karusala,et al. Engaging Identity, Assets, and Constraints in Designing for Resilience , 2019, Proc. ACM Hum. Comput. Interact..
[66] David Nemer,et al. If it Rains, Ask Grandma to Disconnect the Nano , 2019, Proc. ACM Hum. Comput. Interact..
[67] Munmun De Choudhury,et al. Who is the "Human" in Human-Centered Machine Learning , 2019, Proc. ACM Hum. Comput. Interact..
[68] Lauren Wilcox,et al. "Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making , 2019, Proc. ACM Hum. Comput. Interact..
[69] Christopher Frauenberger,et al. Agency of Autistic Children in Technology Research—A Critical Literature Review , 2019, ACM Trans. Comput. Hum. Interact..
[70] Vivek Raghavan,et al. India stack---digital infrastructure as public good , 2019, Commun. ACM.
[71] Gwo-Jen Hwang,et al. Trends and development in technology-enhanced adaptive/personalized learning: A systematic review of journal publications from 2007 to 2017 , 2019, Comput. Educ..
[72] Naveen K. Chilamkurti,et al. Biomedical data analytics in mobile-health environments for high-risk pregnancy outcome prediction , 2019, Journal of Ambient Intelligence and Humanized Computing.
[73] Nicole Wetsman. Artificial intelligence aims to improve cancer screenings in Kenya , 2019, Nature Medicine.
[74] Pradeep Singh,et al. A rule extraction approach from support vector machines for diagnosing hypertension among diabetics , 2019, Expert Syst. Appl..
[75] Ravi Vadlamani,et al. Applications of machine learning techniques to predict filariasis using socio-economic factors , 2019, Epidemiology and Infection.
[76] Mahmood Akhtar,et al. A dynamic neural network model for predicting risk of Zika in real time , 2019, BMC Medicine.
[77] Abdur Rehman Shah. Winners take all: the elite charade of changing the world , 2019, International Affairs.
[78] A. Madabhushi,et al. Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology , 2019, Nature Reviews Clinical Oncology.
[79] Shuguang Yuan,et al. Advancing Drug Discovery via Artificial Intelligence. , 2019, Trends in pharmacological sciences.
[80] Ming Zhou,et al. Intelligent Service System Design of Food Therapy Experience into Chronic Disease , 2019, HCI.
[81] Kaushik Kunal Singh,et al. An Artificial Intelligence based mobile solution for early detection of valvular heart diseases , 2019, 2019 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT).
[82] Yi Pan,et al. Deep Learning for Asphyxiated Infant Cry Classification Based on Acoustic Features and Weighted Prosodic Features , 2019, 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).
[83] Alejandro Baldominos Gómez,et al. Infection Diagnosis using Biomedical Signals in Small Data Scenarios , 2019, 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS).
[84] Andrew McCallum,et al. Energy and Policy Considerations for Deep Learning in NLP , 2019, ACL.
[85] Vicente García-Díaz,et al. A neural network approach to predict early neonatal sepsis , 2019, Comput. Electr. Eng..
[86] Mary L. Gray,et al. Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass , 2019 .
[87] Neha Kumar,et al. Empowerment on the Margins: The Online Experiences of Community Health Workers , 2019, CHI.
[88] David Nemer,et al. "They Don't Leave Us Alone Anywhere We Go": Gender and Digital Abuse in South Asia , 2019, CHI.
[89] Paul N. Bennett,et al. Guidelines for Human-AI Interaction , 2019, CHI.
[90] Tien Yin Wong,et al. Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study. , 2019, The Lancet. Digital health.
[91] Nithya Sambasivan. The remarkable illusions of technology for social good , 2019, Interactions.
[92] John Zimmerman,et al. Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes , 2019, CHI.
[93] Bram van Ginneken,et al. Automated Fetal Head Detection and Circumference Estimation from Free-Hand Ultrasound Sweeps Using Deep Learning in Resource-Limited Countries. , 2019, Ultrasound in medicine & biology.
[94] P. Arora. The Next Billion Users , 2019 .
[95] Milind Tambe,et al. Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data , 2019, KDD.
[96] Siti Nurulain Mohd Rum,et al. Artificial Intelligence in Diagnosing Tuberculosis: A Review , 2019, International Journal on Advanced Science, Engineering and Information Technology.
[97] Shoshana Zuboff. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power , 2019 .
[98] Nicola Dell,et al. Opportunities and challenges in connecting care recipients to the community health feedback loop , 2019, ICTD.
[99] Nithya Sambasivan,et al. Toward responsible AI for the next billion users , 2018, Interactions.
[100] D. van Klaveren,et al. A prediction model for neonatal mortality in low- and middle-income countries: an analysis of data from population surveillance sites in India, Nepal and Bangladesh , 2018, International journal of epidemiology.
[101] S. Davies,et al. Artificial Intelligence in Global Health , 2019, Ethics & International Affairs.
[102] J. Bryson. The Past Decade and Future of AI’s Impact on Society , 2019 .
[103] The Lancet Public Health. Next generation public health: towards precision and fairness. , 2019, The Lancet. Public health.
[104] Olugbenga Oluwagbemi,et al. Implementation of a TCM-based computational health informatics diagnostic tool for Sub-Saharan African students , 2019, Informatics in Medicine Unlocked.
[105] Shivaram Kalyanakrishnan,et al. Opportunities and Challenges for Artificial Intelligence in India , 2018, AIES.
[106] David Danks,et al. Impacts on Trust of Healthcare AI , 2018, AIES.
[107] William Herlands,et al. Proceedings of NeurIPS 2018 Workshop on Machine Learning for the Developing World: Achieving Sustainable Impact , 2018, ArXiv.
[108] Sasank Chilamkurthy,et al. Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study , 2018, The Lancet.
[109] E. Vayena,et al. Machine learning in medicine: Addressing ethical challenges , 2018, PLoS medicine.
[110] Naveena Karusala,et al. Bridging Disconnected Knowledges for Community Health , 2018, Proc. ACM Hum. Comput. Interact..
[111] Neha Kumar,et al. Engaging Solidarity in Data Collection Practices for Community Health , 2018, Proc. ACM Hum. Comput. Interact..
[112] Erick Oduor,et al. Medication Management Companion (MMC) for a Rural Kenyan Community , 2018, CSCW Companion.
[113] Kira Goldner,et al. Mechanism design for social good , 2018, SIGAI.
[114] Hannah Lebovits. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor , 2018, Public Integrity.
[115] Isaac Holeman,et al. Improving Community Health Worker performance by using a personalised feedback dashboard for supervision: a randomised controlled trial , 2018, Journal of global health.
[116] M. Ahmed,et al. Seasonal behavior and forecasting trends of tuberculosis incidence in Holy Kerbala, Iraq , 2018, International journal of mycobacteriology.
[117] Kai-Fu Lee. AI Superpowers: China, Silicon Valley, and the New World Order , 2018 .
[118] Subhash Chandir,et al. Using Predictive Analytics to Identify Children at High Risk of Defaulting From a Routine Immunization Program: Feasibility Study , 2018, JMIR public health and surveillance.
[119] M. Abràmoff,et al. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices , 2018, npj Digital Medicine.
[120] Mariarosaria Taddeo,et al. How AI can be a force for good , 2018, Science.
[121] Stefan Germann,et al. Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings? , 2018, BMJ Global Health.
[122] Yongqing Nan,et al. A machine learning method to monitor China’s AIDS epidemics with data from Baidu trends , 2018, PloS one.
[123] Paul A. Gastañaduy,et al. Public health responses during measles outbreaks in elimination settings: Strategies and challenges , 2018, Human vaccines & immunotherapeutics.
[124] D. Fitch,et al. Review of "Algorithms of oppression: how search engines reinforce racism," by Noble, S. U. (2018). New York, New York: NYU Press. , 2018, CDQR.
[125] Chengyu Liu,et al. Improving the Quality of Point of Care Diagnostics with Real-Time Machine Learning in Low Literacy LMIC Settings , 2018, COMPASS.
[126] Richard J. Anderson,et al. Male Partner Engagement in Family Planning SMS Conversations at Kenyan Health Clinics , 2018, COMPASS.
[127] Wei Yan,et al. Neural Network Based Clinical Treatment Decision Support System for Co-existing Medical Conditions , 2018, 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC).
[128] J. Stringer,et al. Improving preterm newborn identification in low-resource settings with machine learning , 2018, bioRxiv.
[129] David Nemer,et al. El Paquete Semanal: The Week's Internet in Havana , 2018, CHI.
[130] A. Escobar. Designs for the Pluriverse: Radical Interdependence, Autonomy, and the Making of Worlds , 2018 .
[131] D. Jiang,et al. Mapping the spatial distribution of Aedes aegypti and Aedes albopictus. , 2018, Acta tropica.
[132] R. Bodor. Harnessing the power of collective learning: feedback, accountability and constituent voice in rural development , 2018 .
[133] Timnit Gebru,et al. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification , 2018, FAT.
[134] Jianqian Chao,et al. The Impact of the National Essential Medicines Policy on Rational Drug Use in Primary Care Institutions in Jiangsu Province of China , 2018, Iranian journal of public health.
[135] J. A. Oliveira,et al. The Impact of mHealth Interventions: Systematic Review of Systematic Reviews , 2018, JMIR mHealth and uHealth.
[136] L. S. Jayashree,et al. Application of Fuzzy Cognitive Map for geospatial dengue outbreak risk prediction of tropical regions of Southern India , 2018, Intell. Decis. Technol..
[137] B. K. Subramanian,et al. Comparative study to determine the reliability and accuracy of the fetal lite electronic fetal monitor when compared with conventional cardiotocography , 2018, 2018 10th International Conference on Communication Systems & Networks (COMSNETS).
[138] Ehsan Qasemi,et al. Deep Learning Features in Atmospheric Chemistry: Prediction of Cancer Morbidity Due to Air Pollution , 2017, 2017 International Conference on Computational Science and Computational Intelligence (CSCI).
[139] Joyojeet Pal,et al. Changing data practices for community health workers: Introducing digital data collection in West Bengal, India , 2017, ICTD.
[140] L. Taylor. What is data justice? The case for connecting digital rights and freedoms globally , 2017, Big Data Soc..
[141] Tao Liu,et al. Developing a dengue forecast model using machine learning: A case study in China , 2017, PLoS neglected tropical diseases.
[142] Chang Liu,et al. TX-CNN: Detecting tuberculosis in chest X-ray images using convolutional neural network , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[143] Waylon Brunette,et al. Open Data Kit 2.0: A Services-Based Application Framework for Disconnected Data Management , 2017, MobiSys.
[144] Yaniv Kerem,et al. Using Transfer Learning for Improved Mortality Prediction in a Data-Scarce Hospital Setting , 2017, Biomedical informatics insights.
[145] D. Butler. AI summit aims to help world’s poorest , 2017, Nature.
[146] Abhishek Kumar,et al. Utilization of alternative systems of medicine as health care services in India: Evidence on AYUSH care from NSS 2014 , 2017, PloS one.
[147] Melissa Densmore,et al. Video Consumption Patterns for First Time Smartphone Users: Community Health Workers in Lesotho , 2017, CHI.
[148] Ranjit Singh,et al. From Margins to Seams: Imbrication, Inclusion, and Torque in the Aadhaar Identification Project , 2017, CHI.
[149] Nicola Dell,et al. Supporting Community Health Workers in India through Voice- and Web-Based Feedback , 2017, CHI.
[150] W. Keith Edwards,et al. Intersectional HCI: Engaging Identity through Gender, Race, and Class , 2017, CHI.
[151] Cary R. Champlin,et al. AI medicine comes to Africa's rural clinics , 2017, IEEE Spectrum.
[152] Patrick Olivier,et al. Sangoshthi: Empowering Community Health Workers through Peer Learning in Rural India , 2017, WWW.
[153] Shaowen Bardzell,et al. Social Justice and Design: Power and oppression in collaborative systems , 2017, CSCW Companion.
[154] Azuraliza Abu Bakar,et al. Feature selection algorithms for Malaysian dengue outbreak detection model , 2017 .
[155] Alcinês da Silva Sousa,et al. Space-temporal analysis of Chagas disease and its environmental and demographic risk factors in the municipality of Barcarena, Pará, Brazil. , 2017, Revista brasileira de epidemiologia = Brazilian journal of epidemiology.
[156] Sharathkumar Anbu,et al. Machine learning approach for predicting womens health risk , 2017, 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS).
[157] Andrew W. Cross,et al. 99DOTS: Using Mobile Phones to Monitor Adherence to Tuberculosis Medications , 2016 .
[158] Juan Carlos Martínez Santos,et al. Early Prediction of Severe Maternal Morbidity Using Machine Learning Techniques , 2016, IBERAMIA.
[159] Ning Zhang,et al. Improving Tuberculosis Diagnostics Using Deep Learning and Mobile Health Technologies among Resource-Poor and Marginalized Communities , 2016, 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).
[160] Syed Ishtiaque Ahmed,et al. Computing beyond gender-imposed limits , 2016, LIMITS.
[161] Hao Liang,et al. Application of a Combined Model with Autoregressive Integrated Moving Average (ARIMA) and Generalized Regression Neural Network (GRNN) in Forecasting Hepatitis Incidence in Heng County, China , 2016, PloS one.
[162] Aaditeshwar Seth,et al. Design Lessons from Creating a Mobile-based Community Media Platform in Rural India , 2016, ICTD.
[163] Lynn Dombrowski,et al. Social Justice-Oriented Interaction Design: Outlining Key Design Strategies and Commitments , 2016, Conference on Designing Interactive Systems.
[164] Eric C. Larson,et al. SpiroCall: Measuring Lung Function over a Phone Call , 2016, CHI.
[165] Nicola Dell,et al. The Ins and Outs of HCI for Development , 2016, CHI.
[166] B. van Ginneken,et al. An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information , 2016, Scientific Reports.
[167] Fábio Silva Aguiar,et al. Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil , 2016, Medical & Biological Engineering & Computing.
[168] Hyo-Eun Kim,et al. A novel approach for tuberculosis screening based on deep convolutional neural networks , 2016, SPIE Medical Imaging.
[169] C. Pagliari,et al. Effectiveness of mHealth interventions for maternal, newborn and child health in low– and middle–income countries: Systematic review and meta–analysis , 2014, Journal of global health.
[170] Tao Jiang,et al. Android Based Naive Bayes Probabilistic Detection Model for Breast Cancer and Mobile Cloud Computing: Design and Implementation , 2015 .
[171] Neha Kumar,et al. The gender-technology divide or perceptions of non-use? , 2015, First Monday.
[172] M. Shigematsu,et al. Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review , 2015, PloS one.
[173] Madhav V. Marathe,et al. EpiCaster: an integrated web application for situation assessment and forecasting of global epidemics , 2015, BCB.
[174] Kentaro Toyama,et al. Geek Heresy: Rescuing Social Change from the Cult of Technology , 2015 .
[175] Jacki O'Neill,et al. Revisiting CGNet Swara and its impact in rural India , 2015, ICTD.
[176] Richard J. Anderson,et al. Projecting health: community-led video education for maternal health , 2015, ICTD.
[177] Nicola Dell,et al. Engaging Pregnant Women in Kenya with a Hybrid Computer-Human SMS Communication System , 2015, CHI.
[178] Richard J. Anderson,et al. Mobile Phones for Maternal Health in Rural India , 2015, CHI.
[179] Sameer Antani,et al. Lung boundary detection in pediatric chest x-rays , 2015, Medical Imaging.
[180] Teresa Barrio Traspaderne. Encountering Development: The Making and the Unmaking of the Third World , 2015 .
[181] C. Jaffrelot,et al. India’s 2014 Elections. A Modi-led BJP Sweep , 2015 .
[182] Junzhong Gu,et al. Comparative study among three different artificial neural networks to infectious diarrhea forecasting , 2014, 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
[183] Katie Moon,et al. A Guide to Understanding Social Science Research for Natural Scientists , 2014, Conservation biology : the journal of the Society for Conservation Biology.
[184] Sozo Inoue,et al. Evolving health consultancy by predictive caravan health sensing in developing countries , 2014, UbiComp Adjunct.
[185] Neha Kumar,et al. Facebook for self-empowerment? A study of Facebook adoption in urban India , 2014, New Media Soc..
[186] Leonid Roytman,et al. Environmental data analysis and remote sensing for early detection of dengue and malaria , 2014, Sensing Technologies + Applications.
[187] Anirudha N. Joshi,et al. Supporting treatment of people living with HIV / AIDS in resource limited settings with IVRs , 2014, CHI.
[188] K. Denecke,et al. Social Media and Internet-Based Data in Global Systems for Public Health Surveillance: A Systematic Review , 2014, The Milbank quarterly.
[189] Jenna Burrell,et al. Revisiting the fishers of Kerala, India , 2013, ICTD.
[190] Melissa Densmore,et al. Understanding Jugaad: ICTD and the tensions of appropriation, innovation and utility , 2013, ICTD.
[191] Tapan S. Parikh,et al. Understanding barriers to information access and disclosure for HIV+ women , 2013, ICTD.
[192] Mohammed Feham,et al. M-Health: Skin Disease Analysis System Using Smartphone's Camera , 2013, ANT/SEIT.
[193] J. Burrell. Invisible Users: Youth in the Internet Cafés of Urban Ghana , 2012 .
[194] S. Revi Sterling,et al. Considering failure: eight years of ITID research , 2012, ICTD.
[195] S. Waisbord,et al. The handbook of global health communication , 2012 .
[196] Gillian R. Hayes. The relationship of action research to human-computer interaction , 2011, TCHI.
[197] Nithya Sambasivan,et al. The human infrastructure of ICTD , 2010, ICTD.
[198] Gaetano Borriello,et al. Open data kit: tools to build information services for developing regions , 2010, ICTD.
[199] Kentaro Toyama,et al. Where there's a will there's a way: mobile media sharing in urban india , 2010, CHI.
[200] Shaowen Bardzell,et al. Feminist HCI: taking stock and outlining an agenda for design , 2010, CHI.
[201] John F. Canny,et al. Mobile-izing health workers in rural India , 2010, CHI.
[202] K. Toyama,et al. What Constitutes Good ICTD Research , 2009 .
[203] Rajesh Veeraraghavan,et al. Digital Green: Participatory video for agricultural extension , 2007, 2007 International Conference on Information and Communication Technologies and Development.
[204] Susanne Zwingel. Global Feminism: Transnational Women's Activism, Organizing, and Human Rights , 2007 .
[205] N. Yuval‐Davis,et al. Intersectionality and Feminist Politics , 2006 .
[206] V. Braun,et al. Using thematic analysis in psychology , 2006 .
[207] Anne Mills,et al. Complementary and Alternative Medicine -- Disease Control Priorities in Developing Countries , 2006 .
[208] Prasanna Hota,et al. National rural health mission , 2006, Indian journal of pediatrics.
[209] C. Mohanty. “Under Western Eyes” Revisited: Feminist Solidarity through Anticapitalist Struggles , 2003, Signs: Journal of Women in Culture and Society.
[210] E.,et al. ETHNOGRAPHY IN / OF THE WORLD SYSTEM : The Emergence of Multi-Sited Ethnography , 2002 .
[211] S. Merriam. Qualitative research in practice : examples for discussion and analysis , 2002 .
[212] M. F. Jiménez. Encountering Development: The Making and Unmaking of the Third World.Arturo Escobar , 1996 .
[213] Lucy A. Suchman,et al. Making work visible , 1995, CACM.
[214] G. Gutting. The archaeology of knowledge , 1989 .
[215] O. Fals-Borda. The Application of Participatory Action-Research in Latin America , 1987 .