AIMC Topic: Referral and Consultation

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Improved patient satisfaction and diagnostic accuracy in skin diseases with a Visual Clinical Decision Support System-A feasibility study with general practitioners.

PloS one
Patient satisfaction is an important indicator of health care quality, and it remains an important goal for optimal treatment outcomes to reduce the level of misdiagnoses and inappropriate or absent therapeutic actions. Digital support tools for diff...

Artificial Intelligence in Dermatology: A Primer.

The Journal of investigative dermatology
Artificial intelligence is becoming increasingly important in dermatology, with studies reporting accuracy matching or exceeding dermatologists for the diagnosis of skin lesions from clinical and dermoscopic images. However, real-world clinical valid...

Economic Evaluation of Robot-Based Telemedicine Consultation Services.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Through information and communication technology, telemedicine can deliver medical care without time and place restrictions, increasing health care accessibility in medically underdeveloped regions. Although there is growing interest in using robots...

Story Arcs in Serious Illness: Natural Language Processing features of Palliative Care Conversations.

Patient education and counseling
OBJECTIVE: Serious illness conversations are complex clinical narratives that remain poorly understood. Natural Language Processing (NLP) offers new approaches for identifying hidden patterns within the lexicon of stories that may reveal insights abo...

Artificial intelligence and the future of psychiatry: Insights from a global physician survey.

Artificial intelligence in medicine
BACKGROUND: Futurists have predicted that new autonomous technologies, embedded with artificial intelligence (AI) and machine learning (ML), will lead to substantial job losses in many sectors disrupting many aspects of healthcare. Mental health appe...

Triaging ophthalmology outpatient referrals with machine learning: A pilot study.

Clinical & experimental ophthalmology
IMPORTANCE: Triaging of outpatient referrals to ophthalmology services is required for the maintenance of patient care and appropriate resource allocation. Machine learning (ML), in particular natural language processing, may be able to assist with t...

Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

Ophthalmology
PURPOSE: To develop and validate a deep learning (DL) algorithm that predicts referable glaucomatous optic neuropathy (GON) and optic nerve head (ONH) features from color fundus images, to determine the relative importance of these features in referr...

Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.

Epilepsia
Racial disparities in the utilization of epilepsy surgery are well documented, but it is unknown whether a natural language processing (NLP) algorithm trained on physician notes would produce biased recommendations for epilepsy presurgical evaluation...

Assisting radiologists with reporting urgent findings to referring physicians: A machine learning approach to identify cases for prompt communication.

Journal of biomedical informatics
Radiologists are expected to expediently communicate critical and unexpected findings to referring clinicians to prevent delayed diagnosis and treatment of patients. However, competing demands such as heavy workload along with lack of administrative ...