AIMC Topic: Adult

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Severity prediction markers in dengue: a prospective cohort study using machine learning approach.

Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
BACKGROUND: Dengue virus causes illnesses with or without warning indicators for severe complications. There are no clear prognostic signs linked to the disease outcomes.

STANet: A Novel Spatio-Temporal Aggregation Network for Depression Classification with Small and Unbalanced FMRI Data.

Tomography (Ann Arbor, Mich.)
: Early diagnosis of depression is crucial for effective treatment and suicide prevention. Traditional methods rely on self-report questionnaires and clinical assessments, lacking objective biomarkers. Combining functional magnetic resonance imaging ...

Diagnostic potential of salivary microbiota in persistent pulmonary nodules: identifying biomarkers and functional pathways using 16S rRNA sequencing and machine learning.

Journal of translational medicine
BACKGROUND: The aim of this study was to explore the microbial variations and biomarkers in the oral environment of patients with persistent pulmonary nodules (pPNs) and to reveal the potential biological functions of the salivary microbiota in pPNs.

Improving the closing sequences of interaction between human and robot through conversation analysis.

Scientific reports
This study employs Conversation Analysis to create a recursive model that improves the quality of human-robot interaction. Our research goal is to create a dialogue robot that offers pleasant experiences for users, so they are willing to engage in re...

Artificial Intelligence Applications to Measure Food and Nutrient Intakes: Scoping Review.

Journal of medical Internet research
BACKGROUND: Accurate measurement of food and nutrient intake is crucial for nutrition research, dietary surveillance, and disease management, but traditional methods such as 24-hour dietary recalls, food diaries, and food frequency questionnaires are...

Public Perception on Artificial Intelligence-Driven Mental Health Interventions: Survey Research.

JMIR formative research
BACKGROUND: Artificial intelligence (AI) has become increasingly important in health care, generating both curiosity and concern. With a doctor-patient ratio of 1:834 in India, AI has the potential to alleviate a significant health care burden. Publi...

A deep learning approach for automated scoring of the Rey-Osterrieth complex figure.

eLife
Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey-Osterrieth complex figure (ROCF) is the state-of-the-art assessment tool for neuropsychologists across the globe to assess the degree of non-verbal visu...

External validation and performance analysis of a deep learning-based model for the detection of intracranial hemorrhage.

The neuroradiology journal
PurposeWe aimed to investigate the external validation and performance of an FDA-approved deep learning model in labeling intracranial hemorrhage (ICH) cases on a real-world heterogeneous clinical dataset. Furthermore, we delved deeper into evaluatin...

Thickness Speed Progression Index: Machine Learning Approach for Keratoconus Detection.

American journal of ophthalmology
PURPOSE: To develop and validate a pachymetry-based machine learning (ML) index for differentiating keratoconus, keratoconus suspect, and normal corneas.

Rough hypervolume-driven feature selection with groupwise intelligent sampling for detecting clinical characterization of lupus nephritis.

Artificial intelligence in medicine
Systemic lupus erythematosus (SLE) is an autoimmune inflammatory disease. Lupus nephritis (LN) is a major risk factor for morbidity and mortality in SLE. Proliferative and pure membranous LN have different prognoses and may require different treatmen...