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Chronic Disease

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D-UNet: A Dimension-Fusion U Shape Network for Chronic Stroke Lesion Segmentation.

IEEE/ACM transactions on computational biology and bioinformatics
Assessing the location and extent of lesions caused by chronic stroke is critical for medical diagnosis, surgical planning, and prognosis. In recent years, with the rapid development of 2D and 3D convolutional neural networks (CNN), the encoder-decod...

A Machine Learning Approach to the Interpretation of Cardiopulmonary Exercise Tests: Development and Validation.

Pulmonary medicine
OBJECTIVE: At present, there is no consensus on the best strategy for interpreting the cardiopulmonary exercise test's (CPET) results. This study is aimed at assessing the potential of using computer-aided algorithms to evaluate CPET data for identif...

Artificial Intelligence Can Improve Patient Management at the Time of a Pandemic: The Role of Voice Technology.

Journal of medical Internet research
Artificial intelligence-driven voice technology deployed on mobile phones and smart speakers has the potential to improve patient management and organizational workflow. Voice chatbots have been already implemented in health care-leveraging innovativ...

"Looking Under the Hood" of Anchor-Based Assessment of Clinically Important Change: A Machine Learning Approach.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: The Global Assessment of Change (GAC) item has facilitated the interpretation of change in patient-reported outcomes, providing an anchor for computing minimally important differences. Construct validity has been documented via disease-sp...

An anomaly detection approach to identify chronic brain infarcts on MRI.

Scientific reports
The performance of current machine learning methods to detect heterogeneous pathology is limited by the quantity and quality of pathology in medical images. A possible solution is anomaly detection; an approach that can detect all abnormalities by le...

Conversational Agents for Chronic Disease Self-Management: A Systematic Review.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We conducted a systematic literature review to assess how conversational agents have been used to facilitate chronic disease self-management. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was used. Literatu...

Catch Me if You Can: Acute Events Hidden in Structured Chronic Disease Diagnosis Descriptions Show Detectable Recording Patterns in EHR.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Our previous research shows that structured cancer DX description data accuracy varied across electronic health record (EHR) segments (e.g. encounter DX, problem list, etc.). We provide initial evidence corroborating these findings in EHRs from patie...

Machine learning-based multimodal prediction of language outcomes in chronic aphasia.

Human brain mapping
Recent studies have combined multiple neuroimaging modalities to gain further understanding of the neurobiological substrates of aphasia. Following this line of work, the current study uses machine learning approaches to predict aphasia severity and ...

Identifiable Patterns of Trait, State, and Experience in Chronic Stroke Recovery.

Neurorehabilitation and neural repair
BACKGROUND: Considerable evidence indicates that the functional connectome of the healthy human brain is highly stable, analogous to a fingerprint.

Tualang honey versus steroid impregnated nasal dressing following endoscopic sinus surgery: a randomized controlled trial.

Journal of complementary & integrative medicine
OBJECTIVES: Recurrence rate of nasal polyps is high following endoscopic sinus surgery. To improve the surgical outcome, steroid impregnated nasal dressing is used postoperatively We aimed to compare the effect of Tualang honey impregnated nasal dres...