AIMC Topic: Humans

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CKLF and IL1B transcript levels at diagnosis are predictive of relapse in children with pre-B-cell acute lymphoblastic leukaemia.

British journal of haematology
Disease relapse is the greatest cause of treatment failure in paediatric B-cell acute lymphoblastic leukaemia (B-ALL). Current risk stratifications fail to capture all patients at risk of relapse. Herein, we used a machine-learning approach to identi...

Convolutional Neural Network-Based Deep Learning Model for Predicting Differential Suicidality in Depressive Patients Using Brain Generalized q-Sampling Imaging.

The Journal of clinical psychiatry
OBJECTIVE: Suicide is a priority health problem. Suicide assessment depends on imperfect clinician assessment with minimal ability to predict the risk of suicide. Machine learning/deep learning provides an opportunity to detect an individual at risk ...

Assessment of Thoracic Pain Using Machine Learning: A Case Study from Baja California, Mexico.

International journal of environmental research and public health
Thoracic pain is a shared symptom among gastrointestinal diseases, muscle pain, emotional disorders, and the most deadly: Cardiovascular diseases. Due to the limited space in the emergency department, it is important to identify when thoracic pain is...

Observational study on wearable biosensors and machine learning-based remote monitoring of COVID-19 patients.

Scientific reports
Patients infected with SARS-CoV-2 may deteriorate rapidly and therefore continuous monitoring is necessary. We conducted an observational study involving patients with mild COVID-19 to explore the potentials of wearable biosensors and machine learnin...

Computational learning of features for automated colonic polyp classification.

Scientific reports
Shape, texture, and color are critical features for assessing the degree of dysplasia in colonic polyps. A comprehensive analysis of these features is presented in this paper. Shape features are extracted using generic Fourier descriptor. The nonsubs...

Automatic segmentation of inner ear on CT-scan using auto-context convolutional neural network.

Scientific reports
Temporal bone CT-scan is a prerequisite in most surgical procedures concerning the ear such as cochlear implants. The 3D vision of inner ear structures is crucial for diagnostic and surgical preplanning purposes. Since clinical CT-scans are acquired ...

The DecNef collection, fMRI data from closed-loop decoded neurofeedback experiments.

Scientific data
Decoded neurofeedback (DecNef) is a form of closed-loop functional magnetic resonance imaging (fMRI) combined with machine learning approaches, which holds some promises for clinical applications. Yet, currently only a few research groups have had th...

A usability study in patients with stroke using MERLIN, a robotic system based on serious games for upper limb rehabilitation in the home setting.

Journal of neuroengineering and rehabilitation
BACKGROUND: Neuroscience and neurotechnology are transforming stroke rehabilitation. Robotic devices, in addition to telerehabilitation, are increasingly being used to train the upper limbs after stroke, and their use at home allows us to extend inst...