AIMC Topic: Male

Clear Filters Showing 26431 to 26440 of 27433 articles

A telehealth system for automated diagnosis of asthma and chronical obstructive pulmonary disease.

Journal of the American Medical Informatics Association : JAMIA
This paper presents the development and real-time testing of an automated expert diagnostic telehealth system for the diagnosis of 2 respiratory diseases, asthma and Chronic Obstructive Pulmonary Disease (COPD). The system utilizes Android, Java, MAT...

Multivariate Pattern Analysis of Genotype-Phenotype Relationships in Schizophrenia.

Schizophrenia bulletin
Genetic risk variants for schizophrenia have been linked to many related clinical and biological phenotypes with the hopes of delineating how individual variation across thousands of variants corresponds to the clinical and etiologic heterogeneity wi...

Brain Subtyping Enhances The Neuroanatomical Discrimination of Schizophrenia.

Schizophrenia bulletin
Identifying distinctive subtypes of schizophrenia could ultimately enhance diagnostic and prognostic accuracy. We aimed to uncover neuroanatomical subtypes of chronic schizophrenia patients to test whether stratification can enhance computer-aided di...

Disease Definition for Schizophrenia by Functional Connectivity Using Radiomics Strategy.

Schizophrenia bulletin
Specific biomarker reflecting neurobiological substrates of schizophrenia (SZ) is required for its diagnosis and treatment selection of SZ. Evidence from neuroimaging has implicated disrupted functional connectivity in the pathophysiology. We aimed t...

Multisite Machine Learning Analysis Provides a Robust Structural Imaging Signature of Schizophrenia Detectable Across Diverse Patient Populations and Within Individuals.

Schizophrenia bulletin
Past work on relatively small, single-site studies using regional volumetry, and more recently machine learning methods, has shown that widespread structural brain abnormalities are prominent in schizophrenia. However, to be clinically useful, struct...

Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis.

Schizophrenia bulletin
BACKGROUND: The variability of responses to plasticity-inducing repetitive transcranial magnetic stimulation (rTMS) challenges its successful application in psychiatric care. No objective means currently exists to individually predict the patients' r...

Predicting the Ability of Wounds to Heal Given Any Burn Size and Fluid Volume: An Analytical Approach.

Journal of burn care & research : official publication of the American Burn Association
The intrinsic relationship between fluid volume and open wound size (%) has not been previously examined. Therefore, we conducted this study to investigate whether open wound size can be predicted from fluid volume plus other significant factors over...

CT morphological index provides incremental value to machine learning based CT-FFR for predicting hemodynamically significant coronary stenosis.

International journal of cardiology
AIMS: To study the diagnostic performance of the ratio of Duke jeopardy score (DJS) to the minimal lumen diameter (MLD) at coronary computed tomographic angiography (CCTA) and machine learning based CT-FFR for differentiating functionally significant...

Application of a brain-computer interface for person authentication using EEG responses to photo stimuli.

Journal of integrative neuroscience
In this paper, a personal authentication system that can effectively identify individuals by generating unique electroencephalogram signal features in response to self-face and non-self-face photos is presented. To achieve performance stability, a se...

Predicting Language Difficulties in Middle Childhood From Early Developmental Milestones: A Comparison of Traditional Regression and Machine Learning Techniques.

Journal of speech, language, and hearing research : JSLHR
PURPOSE: The current study aimed to compare traditional logistic regression models with machine learning algorithms to investigate the predictive ability of (a) communication performance at 3 years old on language outcomes at 10 years old and (b) bro...