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A Dual-Modal Attention-Enhanced Deep Learning Network for Quantification of Parkinson's Disease Characteristics.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
It is well known that most patients with Parkinson's disease (PD) have different degree of movement disorders, such as shuffling, festination and akinetic episodes, which could degenerate the life quality of PD patients. Therefore, it is very useful ...

A trial on artificial neural networks in predicting sex through bone length measurements on the first and fifth phalanges and metatarsals.

Computers in biology and medicine
BACKGROUND: Predicting sex is an important problem in forensic medicine. The femur, patella, mandible and calcaneus bones are frequently used in predicting sex. In our study, we aimed to use the artificial neural network (ANN) technique to predict se...

CR-Unet: A Composite Network for Ovary and Follicle Segmentation in Ultrasound Images.

IEEE journal of biomedical and health informatics
Transvaginal ultrasound (TVUS) is widely used in infertility treatment. The size and shape of the ovary and follicles must be measured manually for assessing their physiological status by sonographers. However, this process is extremely time-consumin...

Fetal Congenital Heart Disease Echocardiogram Screening Based on DGACNN: Adversarial One-Class Classification Combined with Video Transfer Learning.

IEEE transactions on medical imaging
Fetal congenital heart disease (FHD) is a common and serious congenital malformation in children. In Asia, FHD birth defect rates have reached as high as 9.3%. For the early detection of birth defects and mortality, echocardiography remains the most ...

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.

IEEE transactions on medical imaging
We present a deep convolutional neural network for breast cancer screening exam classification, trained, and evaluated on over 200000 exams (over 1000000 images). Our network achieves an AUC of 0.895 in predicting the presence of cancer in the breast...

GSIAR: gene-subcategory interaction-based improved deep representation learning for breast cancer subcategorical analysis using gene expression, applicable for precision medicine.

Medical & biological engineering & computing
Tumor subclass detection and diagnosis is inevitable requirement for personalized medical treatment and refinement of the effects that the somatic cells show towards other clinical conditions. The genome of these somatic cells exhibits mutations and ...

Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction.

PloS one
One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived....

Development of a Wearable Electrical Impedance Tomographic Sensor for Gesture Recognition With Machine Learning.

IEEE journal of biomedical and health informatics
A wearable electrical impedance tomographic (wEIT) sensor with 8 electrodes is developed to realize gesture recognition with machine learning algorithms. To optimize the wEIT sensor, gesture recognition rates are compared by using a series of electro...

Convolutional Neural Network for Differentiating Gastric Cancer from Gastritis Using Magnified Endoscopy with Narrow Band Imaging.

Digestive diseases and sciences
BACKGROUND: Early detection of early gastric cancer (EGC) allows for less invasive cancer treatment. However, differentiating EGC from gastritis remains challenging. Although magnifying endoscopy with narrow band imaging (ME-NBI) is useful for differ...

Predicting likelihood of psychological disorders in PlayerUnknown's Battlegrounds (PUBG) players from Asian countries using supervised machine learning.

Addictive behaviors
Multiplayer Online Battle Arena (MOBA) has become one of the most popular genre of online video games played by gamers worldwide. Previous studies have exhibited that excessive engagement in games can lead to Internet Gaming Disorder (IGD). Internet ...