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The Digital Distribution of Public Health News Surrounding the Human Papillomavirus Vaccination: A Longitudinal Infodemiology Study

The Digital Distribution of Public Health News Surrounding the Human Papillomavirus Vaccination: A Longitudinal Infodemiology Study

young girls, making it a highly controversial public health debate.While health professionals argue for stronger public health campaigns to promote the HPV vaccination, communication efforts have been challenged on political platforms by US Representative Michele

L Meghan Mahoney, Tang Tang, Kai Ji, Jessica Ulrich-Schad

JMIR Public Health Surveill 2015;1(1):e2

Period of Measurement in Time-Series Predictions of Disease Counts from 2007 to 2017 in Northern Nevada: Analytics Experiment

Period of Measurement in Time-Series Predictions of Disease Counts from 2007 to 2017 in Northern Nevada: Analytics Experiment

Public health surveillance uses ANN to forecast diseases distributions, whereas Guan et al (2004) used ANN to forecast incidents of hepatitis.

Amir Talaei-Khoei, James M Wilson, Seyed-Farzan Kazemi

JMIR Public Health Surveill 2019;5(1):e11357

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Another GA was used in the work of Catalogna et al to support an ANN controller [29].

Ivan Contreras, Josep Vehi

J Med Internet Res 2018;20(5):e10775

Structural Basis for Designing Multiepitope Vaccines Against COVID-19 Infection: In Silico Vaccine Design and Validation

Structural Basis for Designing Multiepitope Vaccines Against COVID-19 Infection: In Silico Vaccine Design and Validation

/498 (97.39)–0.06279NontoxicB44:02Consensus (ann/smm)0.06N protein9KPRQKRTAT487/498 (97.79)–0.20542NontoxicB07:02Consensus(ann/smm/comblib_sidney2008)0.1orf109MGYINVFAF477/480 (99.38)–0.09452NontoxicB35:01Consensus(ann/smm/comblib_sidney2008)0.1orf1010GYINVFAFPFe232

Sukrit Srivastava, Sonia Verma, Mohit Kamthania, Rupinder Kaur, Ruchi Kiran Badyal, Ajay Kumar Saxena, Ho-Joon Shin, Michael Kolbe, Kailash C Pandey

JMIR Bioinformatics Biotechnol 2020;1(1):e19371

Peak Outpatient and Emergency Department Visit Forecasting for Patients With Chronic Respiratory Diseases Using Machine Learning Methods: Retrospective Cohort Study

Peak Outpatient and Emergency Department Visit Forecasting for Patients With Chronic Respiratory Diseases Using Machine Learning Methods: Retrospective Cohort Study

The study used 6 indicators, that is ozone, carbon monoxide, PM10 (particulate matter of 10 μm in diameter or smaller), PM25 (particulate matter less than 2.5 μm in diameter), and sulfur dioxide, from Athens, Greece to train the ANN model.

Junfeng Peng, Chuan Chen, Mi Zhou, Xiaohua Xie, Yuqi Zhou, Ching-Hsing Luo

JMIR Med Inform 2020;8(3):e13075

Staging Dementia From Symptom Profiles on a Care Partner Website

Staging Dementia From Symptom Profiles on a Care Partner Website

Artificial Neural Network (ANN) machine-learning techniques could be particularly beneficial in discovering patterns and how they change with disease progression.

Kenneth Rockwood, Matthew Richard, Chris Leibman, Lisa Mucha, Arnold Mitnitski

J Med Internet Res 2013;15(8):e145

Data-Driven Blood Glucose Pattern Classification and Anomalies Detection: Machine-Learning Applications in Type 1 Diabetes

Data-Driven Blood Glucose Pattern Classification and Anomalies Detection: Machine-Learning Applications in Type 1 Diabetes

On the basis of network topology, an ANN is mainly categorized as a feedforward ANN (single-layer perceptron (SLP), multi-layer perceptron (MLP), and radial basis function [RBF]) and feedback ANN (recurrent neural network [RNN], Elman net, Kohonen’s self-organizing

Ashenafi Zebene Woldaregay, Eirik Årsand, Taxiarchis Botsis, David Albers, Lena Mamykina, Gunnar Hartvigsen

J Med Internet Res 2019;21(5):e11030

Prognostic Modeling of COVID-19 Using Artificial Intelligence in the United Kingdom: Model Development and Validation

Prognostic Modeling of COVID-19 Using Artificial Intelligence in the United Kingdom: Model Development and Validation

These data points represented a feature set that was then used as the input for the ANN. Information regarding patient ethnicity was not felt to be robust due to 23.4% missing data.

Ahmed Abdulaal, Aatish Patel, Esmita Charani, Sarah Denny, Nabeela Mughal, Luke Moore

J Med Internet Res 2020;22(8):e20259