AIMC Topic: Adult

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From cognitive and clinical substrates to functional profiles: Disentangling heterogeneity in schizophrenia.

Psychiatry research
The relationship between neurocognition and functioning among patients with schizophrenia is well documented. However, integrating neuropsychological, clinical and psychopathological data to better investigate functional outcome still constitutes a c...

Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy.

Nature communications
Analysis of sleep for the diagnosis of sleep disorders such as Type-1 Narcolepsy (T1N) currently requires visual inspection of polysomnography records by trained scoring technicians. Here, we used neural networks in approximately 3,000 normal and abn...

Bidirectional Recurrent Auto-Encoder for Photoplethysmogram Denoising.

IEEE journal of biomedical and health informatics
Photoplethysmography (PPG) has become ubiquitous with the development of smart watches and the mobile healthcare market. However, PPG is vulnerable to various types of noises that are ever present in uncontrolled environments, and the key to obtainin...

Exploring the interactions between serum free fatty acids and fecal microbiota in obesity through a machine learning algorithm.

Food research international (Ottawa, Ont.)
Serum free fatty acids (FFA) are generally elevated in obesity. The gut microbiota is involved in the host energy metabolism through the regulation of body fat storage, and a link between diet, FFA and the intestinal microbiota seems to exist. Our ai...

Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Clusters of differentiation () are cell surface biomarkers that denote key biological differences between cell types and disease state. CD-targeting therapeutic monoclonal antibodies () afford rich trans-disease repositioning opportunities. Within a ...

SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Blood hemoglobin level (Hgb) measurement has a vital role in the diagnosis, evaluation, and management of numerous diseases. We describe the use of smartphone video imaging and an artificial neural network (ANN) system to estimate Hgb levels non-inva...

Applying Machine Learning to Linked Administrative and Clinical Data to Enhance the Detection of Homelessness among Vulnerable Veterans.

AMIA ... Annual Symposium proceedings. AMIA Symposium
U.S. military veterans who were discharged from service for misconduct are at high risk for homelessness. Stratifying homelessness risk based on both military service factors and clinical characteristics could facilitate targeted provision of prevent...

A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning per...

Ascertaining Depression Severity by Extracting Patient Health Questionnaire-9 (PHQ-9) Scores from Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The Patient Health Questionnaire-9 (PHQ-9) is a validated instrument for assessing depression severity. While some electronic health record (EHR) systems capture PHQ-9 scores in a structured format, unstructured clinical notes remain the only source ...