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Assessing outcomes of ear molding therapy by health care providers and convolutional neural network.

Scientific reports
Ear molding therapy is a nonsurgical technique to correct certain congenital auricular deformities. While the advantages of nonsurgical treatments over otoplasty are well-described, few studies have assessed aesthetic outcomes. In this study, we comp...

Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal.

Journal of medical Internet research
BACKGROUND: Research on the integration of artificial intelligence (AI) into community-based primary health care (CBPHC) has highlighted several advantages and disadvantages in practice regarding, for example, facilitating diagnosis and disease manag...

Nothing about us without us: involving patient collaborators for machine learning applications in rheumatology.

Annals of the rheumatic diseases
Novel machine learning methods open the door to advances in rheumatology through application to complex, high-dimensional data, otherwise difficult to analyse. Results from such efforts could provide better classification of disease, decision support...

Medical recommender systems based on continuous-valued logic and multi-criteria decision operators, using interpretable neural networks.

BMC medical informatics and decision making
BACKGROUND: Out of the pressure of Digital Transformation, the major industrial domains are using advanced and efficient digital technologies to implement processes that are applied on a daily basis. Unfortunately, this still does not happen in the s...

Understanding providers' attitudes and key concerns toward incorporating CVD risk prediction into clinical practice: a qualitative study.

BMC health services research
BACKGROUND: Although risk prediction has become an integral part of clinical practice guidelines for cardiovascular disease (CVD) prevention, multiple studies have shown that patients' risk still plays almost no role in clinical decision-making. Beca...

Gaining Insights Into Patient Satisfaction Through Interpretable Machine Learning.

IEEE journal of biomedical and health informatics
Patient satisfaction is a key performance indicator of patient-centered care and hospital reimbursement. To discover the major factors that affect patient experiences is considered as an effective way to formulate corrective actions. A patient during...

Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa.

The Pan African medical journal
In sub-Saharan Africa, there is a significant unmet need for emergency care, with a shortage of trained providers. One model to increase the number of providers is to task-share: roles traditionally filled by clinicians are shared with lay workers wh...

Knowledge Extraction of Cohort Characteristics in Research Publications.

AMIA ... Annual Symposium proceedings. AMIA Symposium
When healthcare providers review the results of a clinical trial study to understand its applicability to their practice, they typically analyze how well the characteristics of the study cohort correspond to those of the patients they see. We have pr...

Customer Centricity in Medical Affairs Needs Human-centric Artificial Intelligence.

Pharmaceutical medicine
The evolution of healthcare, together with the changing behaviour of healthcare professionals, means that medical affairs functions of pharmaceutical organisations are constantly reinventing themselves. The emergence of digital ways of working, exped...

How Can Reasoned Transparency Enhance Co-Creation in Healthcare and Remedy the Pitfalls of Digitization in Doctor-Patient Relationships?

International journal of health policy and management
This article addresses transparency in the current era of digital co-creation between healthcare professionals and patients. The concept of reasoned transparency is presented as a potential tool to guide the development of digital co-creation that is...