AIMC Topic: Child

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Diagnosis and Screening of Velocardiofacial Syndrome by Evaluating Facial Photographs Using a Deep Learning-Based Algorithm.

Plastic and reconstructive surgery
BACKGROUND: Early detection of rare genetic diseases, including velocardiofacial syndrome (VCFS), is essential for patient well-being. However, the rarity of these diseases and limited clinical experience of physicians make diagnosis challenging. Dee...

Molecular profiling of blood plasma-derived extracellular vesicles derived from Duchenne muscular dystrophy patients through integration of FTIR spectroscopy and machine learning reveals disease signatures.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
PURPOSE: To identify and monitor the FTIR spectral signatures of plasma extracellular vesicles (EVs) from Duchenne Muscular Dystrophy (DMD) patients at different stages with Healthy controls using machine learning models.

Using machine learning modeling to identify childhood abuse victims on the basis of personality inventory responses.

Journal of psychiatric research
Trauma is very common and associated with significant co-morbidity world-wide, particularly PTSD and frequently other mental health disorders. However, it can be challenging to identify victims of abuse as self-reports can be difficult to elicit due ...

Artificial intelligence-based digital pathology for the detection and quantification of soil-transmitted helminths eggs.

PLoS neglected tropical diseases
BACKGROUND: Conventional microscopy of Kato-Katz (KK1.0) thick smears, the primary method for diagnosing soil-transmitted helminth (STH) infections, has limited sensitivity and is error-prone. Artificial intelligence-based digital pathology (AI-DP) m...

COVID-19 from symptoms to prediction: A statistical and machine learning approach.

Computers in biology and medicine
During the COVID-19 pandemic, the analysis of patient data has become a cornerstone for developing effective public health strategies. This study leverages a dataset comprising over 10,000 anonymized patient records from various leading medical insti...

Development and validation of a deep learning-based survival prediction model for pediatric glioma patients: A retrospective study using the SEER database and Chinese data.

Computers in biology and medicine
OBJECTIVE: Develop a time-dependent deep learning model to accurately predict the prognosis of pediatric glioma patients, which can assist clinicians in making precise treatment decisions and reducing patient risk.

Transfer learning-enabled outcome prediction for guiding CRRT treatment of the pediatric patients with sepsis.

BMC medical informatics and decision making
Continuous renal replacement therapy (CRRT) is a life-saving procedure for sepsis but the benefit of CRRT varies and prediction of clinical outcomes is valuable in efficient treatment planning. This study aimed to use machine learning (ML) models tra...

Interpretable machine learning for allergic rhinitis prediction among preschool children in Urumqi, China.

Scientific reports
This study aimed to investigate the advantages and applications of machine learning models in predicting the risk of allergic rhinitis (AR) in children aged 2-8, compared to traditional logistic regression. The study analyzed questionnaire data from ...