Informatics and technology in clinical care and public health /

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: International Conference on Informatics, Management, and Technology in Healthcare Online
Otros Autores: Mantas, J. (John) (Editor )
Formato: Electrónico Congresos, conferencias eBook
Idioma:Inglés
Publicado: Amsterdam, Netherlands : IOS Press, 2022.
Colección:Studies in health technology and informatics ; v. 289.
Temas:
Medical informatics > Congresses.
COVID-19 (Disease) > Congresses.
Virus diseases > Congresses.
COVID-19 (Disease)
Public health.
COVID-19
Public Health
Médecine > Informatique > Congrès.
COVID-19 > Congrès.
Maladies à virus > Congrès.
COVID-19.
Santé publique.
public health.
Medical informatics
Public health
Virus diseases
Conference papers and proceedings
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Title Page
  • Preface
  • ICIMTH 2021 Scientific Programme Committee and Reviewers
  • Contents
  • Using Artificial Intelligence to Develop a Lexicon-Based African American Tweet Detection Algorithm to Inform Culturally Sensitive Twitter-Based Social Support Interventions for African American Dementia Caregivers
  • A Comparison of Word Embeddings to Study Complications in Neurosurgery
  • Gulf Cooperation Council Clinical Trials in the Pursuit of Medications for COVID-19
  • Hazards for the Implementation and Use of Artificial Intelligence Enabled Digital Health Interventions, a UK Perspective
  • An Evaluation of Pretrained BERT Models for Comparing Semantic Similarity Across Unstructured Clinical Trial Texts
  • AI Enhanced Person-Centred Care Services for Monitoring Stroke Outpatient Rehabilitation
  • FAIR and Quality Assured Data
  • The Use Case of Trueness
  • Using Machine Learning to Improve Personalised Prediction: A Data-Driven Approach to Segment and Stratify Populations for Healthcare
  • Prediction of Postoperative Speech Dysfunction Based on Cortico-Cortical Evoked Potentials and Machine Learning
  • Early Prediction of Neoplasms Using Machine Learning: A Study of Electronic Health Records from the Ministry of National Guard Health Affairs in Saudi Arabia
  • Medical Informatics in a Tension Between Black-Box AI and Trust
  • Development of an Expert Knowledge-Based Genomic Variant Prioritisation Platform
  • Pro-Active Detection of Potentially Wrong Diagnoses Due to Substantial Changes of Laboratory Measurements
  • The Clinical and Biochemical Parameter Data: Effect of High Blood Glucose on Diabetic Nephropathy Among Non-Insulin-Dependent Diabetes Mellitus (NIDDM), Thailand
  • Public Sentiment Towards Vaccination After COVID-19 Outbreak in the Arab World
  • ABiMed: Towards an Innovative Clinical Decision Support System for Medication Reviews and Polypharmacy Management
  • Machine Learning Approaches for Early Prostate Cancer Prediction Based on Healthcare Utilization Patterns
  • Semiautomatic Identification of Pulmonary Embolism in Electronic Health Records Through Sentence Labeling
  • Utilizing Shared Big Data to Identify Liver Cancer Dedifferentiation Markers
  • ALLD: Acute Lymphoblastic Leukemia Detector
  • Application of Natural Language Processing to Learn Insights on the Clinician's Lived Experience of Electronic Health Records
  • Healthcare Professionals' Perceptions and Opinions on ""Do not Attempt Resuscitation"" (DNAR) Order and Documentation
  • A Framework for User-Configurable Data Quality Assurance of Electronic Patient Records
  • Predicting the Risk Factors of Second Primary Cancer in Patients with Hepatocellular Carcinoma

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