AIMC Topic: Humans

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Embedding Weather Simulation in Auto-Labelling Pipelines Improves Vehicle Detection in Adverse Conditions.

Sensors (Basel, Switzerland)
The performance of deep learning-based detection methods has made them an attractive option for robotic perception. However, their training typically requires large volumes of data containing all the various situations the robots may potentially enco...

Applying Deep Learning for Breast Cancer Detection in Radiology.

Current oncology (Toronto, Ont.)
Recent advances in deep learning have enhanced medical imaging research. Breast cancer is the most prevalent cancer among women, and many applications have been developed to improve its early detection. The purpose of this review is to examine how va...

Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases.

Scientific reports
Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-b...

Identification of texture MRI brain abnormalities on first-episode psychosis and clinical high-risk subjects using explainable artificial intelligence.

Translational psychiatry
Structural MRI studies in first-episode psychosis and the clinical high-risk state have consistently shown volumetric abnormalities. Aim of the present study was to introduce radiomics texture features in identification of psychosis. Radiomics textur...

Personalized prediction of optimal water intake in adult population by blended use of machine learning and clinical data.

Scientific reports
Growing evidence suggests that sustained concentrated urine contributes to chronic metabolic and kidney diseases. Recent results indicate that a daily urinary concentration of 500 mOsm/kg reflects optimal hydration. This study aims at providing perso...

Automated patient-robot assignment for a robotic rehabilitation gym: a simplified simulation model.

Journal of neuroengineering and rehabilitation
BACKGROUND: A robotic rehabilitation gym can be defined as multiple patients training with multiple robots or passive sensorized devices in a group setting. Recent work with such gyms has shown positive rehabilitation outcomes; furthermore, such gyms...

Estimating critical values from electrocardiogram using a deep ordinal convolutional neural network.

BMC medical informatics and decision making
BACKGROUND: Critical values are commonly used in clinical laboratory tests to define health-related conditions of varying degrees. Knowing the values, people can quickly become aware of health risks, and the health professionals can take immediate ac...

Evaluation of word embedding models to extract and predict surgical data in breast cancer.

BMC bioinformatics
BACKGROUND: Decisions in healthcare usually rely on the goodness and completeness of data that could be coupled with heuristics to improve the decision process itself. However, this is often an incomplete process. Structured interviews denominated De...

Facial features of lysosomal storage disorders.

Expert review of endocrinology & metabolism
INTRODUCTION: The use of facial recognition technology has diversified the diagnostic toolbelt for clinicians and researchers for the accurate diagnoses of patients with rare and challenging disorders. Specific identifiers in patient images can be gr...

Calibrated bagging deep learning for image semantic segmentation: A case study on COVID-19 chest X-ray image.

PloS one
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Imaging tests such as chest X-ray (CXR) and computed tomography (CT) can provide useful information to clinical staff for facilitating a diagnosi...