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Stem-cell based, machine learning approach for optimizing natural killer cell-based personalized immunotherapy for high-grade ovarian cancer.

The FEBS journal
Advanced high-grade serous ovarian cancer continues to be a therapeutic challenge for those affected using the current therapeutic interventions. There is an increasing interest in personalized cancer immunotherapy using activated natural killer (NK)...

Diagnosing thyroid nodules with atypia of undetermined significance/follicular lesion of undetermined significance cytology with the deep convolutional neural network.

Scientific reports
To compare the diagnostic performances of physicians and a deep convolutional neural network (CNN) predicting malignancy with ultrasonography images of thyroid nodules with atypia of undetermined significance (AUS)/follicular lesion of undetermined s...

Predicting cognitive impairment in outpatients with epilepsy using machine learning techniques.

Scientific reports
Many studies report predictions for cognitive function but there are few predictions in epileptic patients; therefore, we established a workflow to efficiently predict outcomes of both the Mini-Mental State Examination (MMSE) and Montreal Cognitive A...

Annotation-efficient deep learning for automatic medical image segmentation.

Nature communications
Automatic medical image segmentation plays a critical role in scientific research and medical care. Existing high-performance deep learning methods typically rely on large training datasets with high-quality manual annotations, which are difficult to...

Deep learning based multiplexed sensitivity-encoding (DL-MUSE) for high-resolution multi-shot DWI.

NeuroImage
PURPOSE: A phase correction method for high-resolution multi-shot (MSH) diffusion weighted imaging (DWI) is proposed. The efficacy and generalization capability of the method were validated on both healthy volunteers and patients.

Smartphone-Based Human Sitting Behaviors Recognition Using Inertial Sensor.

Sensors (Basel, Switzerland)
At present, people spend most of their time in passive rather than active mode. Sitting with computers for a long time may lead to unhealthy conditions like shoulder pain, numbness, headache, etc. To overcome this problem, human posture should be cha...

A bioinspired neural architecture search based convolutional neural network for breast cancer detection using histopathology images.

Scientific reports
The design of neural architecture to address the challenge of detecting abnormalities in histopathology images can leverage the gains made in the field of neural architecture search (NAS). The NAS model consists of a search space, search strategy and...

A machine learning model to predict critical care outcomes in patient with chest pain visiting the emergency department.

BMC emergency medicine
BACKGROUND: Currently, the risk stratification of critically ill patient with chest pain is a challenge. We aimed to use machine learning approach to predict the critical care outcomes in patients with chest pain, and simultaneously compare its perfo...

Subject-Independent Emotion Recognition of EEG Signals Based on Dynamic Empirical Convolutional Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
Affective computing is one of the key technologies to achieve advanced brain-machine interfacing. It is increasingly concerning research orientation in the field of artificial intelligence. Emotion recognition is closely related to affective computin...

Advanced Machine-Learning Methods for Brain-Computer Interfacing.

IEEE/ACM transactions on computational biology and bioinformatics
The brain-computer interface (BCI) connects the brain and the external world through an information transmission channel by interpreting the physiological information of the brain during thinking activities. The effective classification of electroenc...