The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review
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C. Wiysonge | J. Okeibunor | E. Mavundza | A. Jaca | Ngozi Idemili-Aronu | Derrick Muneene | L. Makubalo | C. Iwu-Jaja | Housseynou Ba | Z. P. Zantsi | A. M. Ndlambe
[1] Teresa Angela Trunfio,et al. Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy , 2022, BMC Medical Informatics and Decision Making.
[2] J. Ong,et al. A Machine-Learning-Based Risk-Prediction Tool for HIV and Sexually Transmitted Infections Acquisition over the Next 12 Months , 2022, Journal of clinical medicine.
[3] Sijia Zhou,et al. Application of Artificial Intelligence on Psychological Interventions and Diagnosis: An Overview , 2022, Frontiers in Psychiatry.
[4] V. Visconte,et al. Personalized Risk Schemes and Machine Learning to Empower Genomic Prognostication Models in Myelodysplastic Syndromes , 2022, International journal of molecular sciences.
[5] N. Aslam. Explainable Artificial Intelligence Approach for the Early Prediction of Ventilator Support and Mortality in COVID-19 Patients , 2022, Comput..
[6] J. Delhommelle,et al. Machine Learning and Deep Learning Algorithms for Skin Cancer Classification from Dermoscopic Images , 2022, Bioengineering.
[7] C. Reinhold,et al. Radiomics and machine learning for the diagnosis of pediatric cervical non-tuberculous mycobacterial lymphadenitis , 2022, Scientific Reports.
[8] Mengying Wang,et al. Deep learning model for multi-classification of infectious diseases from unstructured electronic medical records , 2022, BMC Medical Informatics and Decision Making.
[9] F. Harrou,et al. A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models , 2022, Scientific Reports.
[10] F. Moraes,et al. An overview of artificial intelligence in oncology , 2022, Future science OA.
[11] A. Mohammed,et al. Improving classification accuracy for prostate cancer using noise removal filter and deep learning technique , 2022, Multimedia Tools and Applications.
[12] D. Heider,et al. Evaluation of machine learning strategies for imaging confirmed prostate cancer recurrence prediction on electronic health records , 2022, Comput. Biol. Medicine.
[13] H. Chiroma,et al. Improved multi-classification of breast cancer histopathological images using handcrafted features and deep neural network (dense layer) , 2022, Intell. Syst. Appl..
[14] P. Keane,et al. Teleophthalmology-enabled and artificial intelligence-ready referral pathway for community optometry referrals of retinal disease (HERMES): a Cluster Randomised Superiority Trial with a linked Diagnostic Accuracy Study—HERMES study report 1—study protocol , 2022, BMJ Open.
[15] Md Belal Bin Heyat,et al. Frontal lobe real-time EEG analysis using machine learning techniques for mental stress detection. , 2022, Journal of integrative neuroscience.
[16] A. Eleyan,et al. COVID-19 detection on chest radiographs using feature fusion based deep learning , 2022, Signal, Image and Video Processing.
[17] A. Khandoker,et al. Detection of COVID-19 in smartphone-based breathing recordings: A pre-screening deep learning tool , 2022, PloS one.
[18] Omar M. Darwish,et al. An explainable machine learning framework for lung cancer hospital length of stay prediction , 2022, Scientific Reports.
[19] F. Shih,et al. Machine learning for emerging infectious disease field responses , 2022, Scientific Reports.
[20] V. Jeyakumar,et al. Panoramic tongue imaging and deep convolutional machine learning model for diabetes diagnosis in humans , 2022, Scientific Reports.
[21] P. Serruys,et al. Machine learning for atherosclerotic tissue component classification in combined near-infrared spectroscopy intravascular ultrasound imaging: Validation against histology. , 2022, Atherosclerosis.
[22] M. Alazzam,et al. Machine Learning Implementation of a Diabetic Patient Monitoring System Using Interactive E-App , 2021, Comput. Intell. Neurosci..
[23] P. Noseworthy,et al. Development of the AI-Cirrhosis-ECG Score: An Electrocardiogram-Based Deep Learning Model in Cirrhosis , 2021, The American journal of gastroenterology.
[24] N. Holalkere,et al. Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence , 2021, Nature Machine Intelligence.
[25] Yu-xiong Su,et al. Deep Learning Predicts the Malignant-Transformation-Free Survival of Oral Potentially Malignant Disorders , 2021, Cancers.
[26] Jake Luo,et al. Predicting Risk of Stroke From Lab Tests Using Machine Learning Algorithms: Development and Evaluation of Prediction Models , 2021, JMIR formative research.
[27] A. Almazroi. Survival prediction among heart patients using machine learning techniques. , 2021, Mathematical biosciences and engineering : MBE.
[28] Bhavani Singh Agnikula Kshatriya,et al. Identification of asthma control factor in clinical notes using a hybrid deep learning model , 2021, BMC Medical Informatics and Decision Making.
[29] J. Simon,et al. Assessment of lemon juice adulteration by targeted screening using LC-UV-MS and untargeted screening using UHPLC-QTOF/MS with machine learning. , 2021, Food chemistry.
[30] Mazhar Javed Awan,et al. Detection of COVID-19 in Chest X-ray Images: A Big Data Enabled Deep Learning Approach , 2021, International journal of environmental research and public health.
[31] E. Behr,et al. Application of artificial intelligence to the electrocardiogram , 2021, European heart journal.
[32] Catherine Staton,et al. Microplanning for designing vaccination campaigns in low-resource settings: A geospatial artificial intelligence-based framework , 2021, Vaccine.
[33] Abdullah H. Alzeer,et al. Using machine learning to reduce unnecessary rehospitalization of cardiovascular patients in Saudi Arabia , 2021, Int. J. Medical Informatics.
[34] Yi Ji Bae,et al. Schizophrenia Detection Using Machine Learning Approach from Social Media Content , 2021, Sensors.
[35] K. Matsudaira,et al. Effects of an Artificial Intelligence–Assisted Health Program on Workers With Neck/Shoulder Pain/Stiffness and Low Back Pain: Randomized Controlled Trial , 2021, JMIR mHealth and uHealth.
[36] J. Garioch,et al. Machine-learning algorithm to predict multidisciplinary team treatment recommendations in the management of basal cell carcinoma , 2021, British Journal of Cancer.
[37] Dost Muhammad Khan,et al. Prediction of Multidrug-Resistant Tuberculosis Using Machine Learning Algorithms in SWAT, Pakistan , 2021, Journal of healthcare engineering.
[38] Ivo D. Dinov,et al. Modeling and prediction of pressure injury in hospitalized patients using artificial intelligence , 2021, BMC Medical Informatics and Decision Making.
[39] Itzhak Z. Attia,et al. Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model , 2021, European heart journal. Digital health.
[40] Gwanggil Jeon,et al. Enabling Artificial Intelligence for Genome Sequence Analysis of COVID-19 and Alike Viruses , 2021, Interdisciplinary Sciences: Computational Life Sciences.
[41] José Tomás Arenas-Cavalli,et al. Correction: Clinical validation of an artificial intelligence-based diabetic retinopathy screening tool for a national health system , 2021, Eye.
[42] T. Park,et al. A Deep Learning Algorithm to Predict Hazardous Drinkers and the Severity of Alcohol-Related Problems Using K-NHANES , 2021, Frontiers in Psychiatry.
[43] R. Baron. Using Artificial Intelligence to Make Use of Electronic Health Records Less Painful-Fighting Fire With Fire. , 2021, JAMA network open.
[44] Alessandro Monaco,et al. Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases , 2021, Frontiers in Digital Health.
[45] A. Shehab,et al. COVID-19 Diagnosis Using an Enhanced Inception-ResNetV2 Deep Learning Model in CXR Images , 2021, Journal of healthcare engineering.
[46] E. Charani,et al. Clinical Utility and Functionality of an Artificial Intelligence–Based App to Predict Mortality in COVID-19: Mixed Methods Analysis , 2021, JMIR formative research.
[47] Matheus Araujo,et al. Using Deep Learning for Individual-Level Predictions of Adherence with Growth Hormone Therapy , 2021, MIE.
[48] A. Głowacz,et al. A Novel Method for COVID-19 Diagnosis Using Artificial Intelligence in Chest X-ray Images , 2021, Healthcare.
[49] Deepti R. Bathula,et al. Predicting women with depressive symptoms postpartum with machine learning methods , 2021, Scientific Reports.
[50] P. Ferdinandy,et al. Cardiovascular RNA markers and artificial intelligence may improve COVID-19 outcome: a position paper from the EU-CardioRNA COST Action CA17129 , 2021, Cardiovascular research.
[51] Marcus A. Badgeley,et al. Using deep learning algorithms to simultaneously identify right and left ventricular dysfunction from the electrocardiogram. , 2021, medRxiv.
[52] Elizabeth S. Chen,et al. Predicting open wound mortality in the ICU using machine learning , 2021, Journal of emergency and critical care medicine.
[53] Bruno Alberto Soares Oliveira,et al. Explaining machine learning based diagnosis of COVID-19 from routine blood tests with decision trees and criteria graphs , 2021, Computers in Biology and Medicine.
[54] D. Yuvaraj,et al. A study on the role of natural language processing in the healthcare sector , 2021 .
[55] V. Abedi,et al. Prediction of Long-Term Stroke Recurrence Using Machine Learning Models , 2021, Journal of clinical medicine.
[56] Riyad Alshammari,et al. Using Machine Learning to Predict Early Preparation of Pharmacy Prescriptions at PSMMC - a Comparison of Four Machine Learning Algorithms , 2021, Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH.
[57] José Tomás Arenas-Cavalli,et al. Clinical validation of an artificial intelligence-based diabetic retinopathy screening tool for a national health system , 2021, Eye.
[58] J. Baron,et al. Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts , 2021, JAMIA open.
[59] S. N. Payrovnaziri,et al. Machine learning-based prediction of health outcomes in pediatric organ transplantation recipients. , 2021, JAMIA open.
[60] G. Callicó,et al. Analysis of Risk Factors in Dementia Through Machine Learning. , 2020, Journal of Alzheimer's disease : JAD.
[61] J. Soriano,et al. Evidence of Gender Differences in the Diagnosis and Management of Coronavirus Disease 2019 Patients: An Analysis of Electronic Health Records Using Natural Language Processing and Machine Learning. , 2020, Journal of women's health.
[62] Alessandro Blasimme,et al. Explainability for artificial intelligence in healthcare: a multidisciplinary perspective , 2020, BMC Medical Informatics and Decision Making.
[63] Sebastiano Barbieri,et al. Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach , 2020, International journal of epidemiology.
[64] H. Abbasimehr,et al. Prediction of COVID-19 confirmed cases combining deep learning methods and Bayesian optimization , 2020, Chaos, Solitons & Fractals.
[65] M. A. Al-antari,et al. “Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images” , 2020, Applied Intelligence.
[66] C. Fairley,et al. Predicting the diagnosis of HIV and sexually transmitted infections among men who have sex with men using machine learning approaches. , 2020, The Journal of infection.
[67] Marco Piñón,et al. I Overview , 2020, The Diaries and Letters of Lord Woolton 1940-1945.
[68] Sandeep Reddy,et al. Artificial intelligence and healthcare—why they need each other? , 2020 .
[69] A. Barnawi,et al. Machine and Deep Learning Towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions , 2020 .
[70] D. Mollura,et al. Artificial Intelligence in Low- and Middle-Income Countries: Innovating Global Health Radiology. , 2020, Radiology.
[71] Stephen D Auger,et al. Big data, machine learning and artificial intelligence: a neurologist’s guide , 2020, Practical Neurology.
[72] Malay Kishore Dutta,et al. Automatic diagnosis of multiple cardiac diseases from PCG signals using convolutional neural network , 2020, Comput. Methods Programs Biomed..
[73] Sumaiya Tabassum Nimi,et al. Prediction of Lung Function in Adolescence Using Epigenetic Aging: A Machine Learning Approach , 2020, Methods and protocols.
[74] B. Stantic,et al. Efficacy of deep learning methods for predicting under-five mortality in 34 low-income and middle-income countries , 2020, BMJ Open.
[75] Carlos Fernandez-Lozano,et al. Identification of predictive factors of the degree of adherence to the Mediterranean diet through machine-learning techniques , 2020, PeerJ Comput. Sci..
[76] Naeem Ramzan,et al. Triaxial Accelerometer-Based Falls and Activities of Daily Life Detection Using Machine Learning , 2020, Sensors.
[77] Surajit Ray,et al. Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population , 2020, International Immunopharmacology.
[78] Masoud Abdollahi,et al. Using a Motion Sensor to Categorize Nonspecific Low Back Pain Patients: A Machine Learning Approach , 2020, Sensors.
[79] 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.
[80] Laura B. Balzer,et al. Artificial Intelligence and Machine Learning for HIV Prevention: Emerging Approaches to Ending the Epidemic , 2020, Current HIV/AIDS Reports.
[81] Stephen R. Aichele,et al. Predicting Cognitive Impairment and Dementia: A Machine Learning Approach. , 2020, Journal of Alzheimer's disease : JAD.
[82] G. Olinger,et al. Project IDentif.AI: Harnessing Artificial Intelligence to Rapidly Optimize Combination Therapy Development for Infectious Disease Intervention , 2020, Advanced therapeutics.
[83] Michael Gao,et al. Machine learning for early detection of sepsis: an internal and temporal validation study , 2020, JAMIA open.
[84] Gopi Battineni,et al. Applications of Machine Learning Predictive Models in the Chronic Disease Diagnosis , 2020, Journal of personalized medicine.
[85] W. Kostis,et al. Uses and opportunities for machine learning in hypertension research , 2020, International Journal of Cardiology. Hypertension.
[86] Namita Srivastava,et al. The Machine‐Learning Approach , 2020, Machine Learning for iOS Developers.
[87] J. Geddes,et al. Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations , 2020, Evidence-Based Mental Health.
[88] T. Vetter,et al. Linear Regression in Medical Research , 2020, Anesthesia and analgesia.
[89] Mei Chen,et al. Artificial intelligence in healthcare: An essential guide for health leaders , 2019, Healthcare management forum.
[90] Mohamed Alloghani,et al. Implementation of machine learning algorithms to create diabetic patient re-admission profiles , 2019, BMC Medical Informatics and Decision Making.
[91] Ahmed Hosny,et al. Artificial intelligence for global health , 2019, Science.
[92] José Luis Risco-Martín,et al. An application of machine learning with feature selection to improve diagnosis and classification of neurodegenerative disorders , 2019, BMC Bioinformatics.
[93] A. Agarwal,et al. Automation of human semen analysis using a novel artificial intelligence optical microscopic technology , 2019, Andrologia.
[94] Bradley J Erickson,et al. A Survey of Deep-Learning Applications in Ultrasound: Artificial Intelligence-Powered Ultrasound for Improving Clinical Workflow. , 2019, Journal of the American College of Radiology : JACR.
[95] Awais Ashfaq,et al. Readmission prediction using deep learning on electronic health records , 2019, J. Biomed. Informatics.
[96] Alemka Tomicic,et al. Recognizing states of psychological vulnerability to suicidal behavior: a Bayesian network of artificial intelligence applied to a clinical sample , 2019, BMC Psychiatry.
[97] Herbert F. Voigt,et al. IEEE Engineering in Medicine and Biology Society , 2019, IEEE Transactions on Biomedical Engineering.
[98] S. Kalra,et al. Artificial Intelligence/Machine Learning in Diabetes Care , 2019, Indian journal of endocrinology and metabolism.
[99] T. Davenport,et al. The potential for artificial intelligence in healthcare , 2019, Future Healthcare Journal.
[100] Yifan Zhou,et al. Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs , 2019, Comput. Biol. Medicine.
[101] Eric R. LaRose,et al. Machine learning for phenotyping opioid overdose events , 2019, J. Biomed. Informatics.
[102] Nigam H. Shah,et al. Finding missed cases of familial hypercholesterolemia in health systems using machine learning , 2019, npj Digital Medicine.
[103] Garrath T. Wilson,et al. Closing the Loop on E‐waste: A Multidisciplinary Perspective , 2019 .
[104] J. Whitney,et al. Predicting Pressure Injury in Critical Care Patients: A Machine‐Learning Model , 2018, American journal of critical care : an official publication, American Association of Critical-Care Nurses.
[105] Elizabeth S. Chen,et al. Predicting Mortality in Diabetic ICU Patients Using Machine Learning and Severity Indices , 2018, AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science.
[106] Andrew Y. Ng,et al. Improving palliative care with deep learning , 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
[107] Flávio H. D. Araújo,et al. Using machine learning to support healthcare professionals in making preauthorisation decisions , 2016, Int. J. Medical Informatics.
[108] D. Heimburger,et al. A longitudinal study of systemic inflammation and recovery of lean body mass among malnourished HIV-infected adults starting antiretroviral therapy in Tanzania and Zambia , 2016, European Journal of Clinical Nutrition.
[109] Maryam Farhadian,et al. Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach , 2015, International Archives of Occupational and Environmental Health.
[110] Concha Bielza,et al. Bayesian networks in neuroscience: a survey , 2014, Front. Comput. Neurosci..
[111] J. Foster,et al. Machine Learning Techniques Accurately Classify Microbial Communities by Bacterial Vaginosis Characteristics , 2014, PloS one.
[112] 澤頭 毅,et al. (5)33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society参加報告(国際会議案内・報告) , 2011 .
[113] U. Rajendra Acharya,et al. Identification of Cataract and Post-cataract Surgery Optical Images Using Artificial Intelligence Techniques , 2010, Journal of Medical Systems.
[114] Marie des Jardins,et al. Artificial Intelligence: Machine Learning , 2005 .
[115] A. Sanabria,et al. Randomized controlled trial. , 2005, World journal of surgery.
[116] H. Arksey,et al. Scoping studies: towards a methodological framework , 2005 .
[117] H. Baxter Williams,et al. A Survey , 1992 .
[118] Gokhan Altan. DeepOCT: An explainable deep learning architecture to analyze macular edema on OCT images , 2022, Engineering Science and Technology, an International Journal.
[119] S. Sunarti,et al. Artificial intelligence in healthcare: opportunities and risk for future. , 2021, Gaceta sanitaria.
[120] 智晴 長尾,et al. Deep Neural Network を用いた株式売買戦略の構築 , 2016 .
[121] R.N.G. Naguib,et al. Knowledge Creation Using Artificial Intelligence: A Twin Approach to Improve Breast Screening Attendance , 2006, 2006 International Conference of the IEEE Engineering in Medicine and Biology Society.
[122] N. Ibrahim,et al. Covid-19 and Artificial Intelligence: Genome sequencing, drug development and vaccine discovery , 2022, Journal of Infection and Public Health.