AIMC Topic: Adult

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Machine learning models based on ultrasound and physical examination for airway assessment.

Revista espanola de anestesiologia y reanimacion
PURPOSE: To demonstrate the utility of machine learning models for predicting difficult airways using clinical and ultrasound parameters.

Validity of facial skin analysis pore detection: A comparative analysis.

Journal of cosmetic dermatology
BACKGROUND: Reliable, objective measures to assess facial characteristics would aid in the assessment of many dermatological treatments. Previous work utilized an iOS application-based artificial intelligence (AI) tool compared to the "gold standard"...

Construction of the prediction model for multiple myeloma based on machine learning.

International journal of laboratory hematology
INTRODUCTION: The global burden of multiple myeloma (MM) is increasing every year. Here, we have developed machine learning models to provide a reference for the early detection of MM.

Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data.

Journal of affective disorders
BACKGROUND: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presenta...

Deep Learning-Based Segmentation and Risk Stratification for Gastrointestinal Stromal Tumors in Transabdominal Ultrasound Imaging.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
PURPOSE: To develop a deep neural network system for the automatic segmentation and risk stratification prediction of gastrointestinal stromal tumors (GISTs).

No code machine learning: validating the approach on use-case for classifying clavicle fractures.

Clinical imaging
PURPOSE: We created an infrastructure for no code machine learning (NML) platform for non-programming physicians to create NML model. We tested the platform by creating an NML model for classifying radiographs for the presence and absence of clavicle...

Deciphering the environmental chemical basis of muscle quality decline by interpretable machine learning models.

The American journal of clinical nutrition
BACKGROUND: Sarcopenia is known as a decline in skeletal muscle quality and function that is associated with age. Sarcopenia is linked to diverse health problems, including endocrine-related diseases. Environmental chemicals (ECs), a broad class of c...

Predicting treatment resistance in schizophrenia patients: Machine learning highlights the role of early pathophysiologic features.

Schizophrenia research
Detecting patients with a high-risk profile for treatment-resistant schizophrenia (TRS) can be beneficial for implementing individually adapted therapeutic strategies and better understanding the TRS etiology. The aim of this study was to explore, wi...

Development of a machine learning-based prediction model for clinical pregnancy of intrauterine insemination in a large Chinese population.

Journal of assisted reproduction and genetics
PURPOSE: This study aimed to evaluate the effectiveness of a random forest (RF) model in predicting clinical pregnancy outcomes from intrauterine insemination (IUI) and identifying significant factors affecting IUI pregnancy in a large Chinese popula...