Menopause

An Investigation of Various Machine and Deep Learning Techniques Applied in Automatic Fear Level Detection and Acrophobia Virtual Therapy.

In this paper, we investigate various machine learning classifiers used in our Virtual Reality (VR) system for treating acrophobia. The system automatically estimates fear level based on multimodal sensory data and a self-reported emotion assessment. There are two modalities of expressing fear ratings: the 2-choice scale, where 0 represents relaxation and 1 stands for fear; and the 4-choice scale,...

Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records.

Machine learning has become ubiquitous and a key technology on mining electronic health records (EHRs) for facilitating clinical research and practice. Unsupervised machine learning, as opposed to supervised learning, has shown promise in identifying novel patterns and relations from EHRs without using human created labels. In this paper, we investigate the application of unsupervised machine lear...

Sparse Ensemble Machine Learning to Improve Robustness of Long-Term Decoding in iBMIs.

This paper presents a novel sparse ensemble based machine learning approach to enhance robustness of intracortical Brain Machine Interfaces (iBMIs) in...

Predicting breast cancer risk using personal health data and machine learning models.

Among women, breast cancer is a leading cause of death. Breast cancer risk predictions can inform screening and preventative actions. Previous works f...

iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks.

BACKGROUND: Enhancers are non-coding DNA fragments which are crucial in gene regulation (e.g. transcription and translation). Having high locational v...

Predicting the individual risk of psychosis conversion in at-risk mental state (ARMS): a multivariate model reveals the influence of nonpsychotic prodromal symptoms.

To improve the prediction of the individual risk of conversion to psychosis in UHR subjects, by considering all CAARMS' symptoms at first presentation...

Secretion of equine chorionic gonadotropin and its association with supplementary corpus luteum formation and progesterone concentration in Hokkaido native pony recipient mares.

The objectives of this study were to determine the plasma profile of equine chorionic gonadotropin (eCG) and its association with the formation of sup...

Diagnostic and Gradation Model of Osteoporosis Based on Improved Deep U-Net Network.

The measurement of bone mineral density for osteoporosis has always been the focus of researchers because it plays an important role in bone disease d...

The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population.

OBJECTIVE: Osteoporosis is hard to detect before it manifests symptoms and complications. In this study, we evaluated machine learning models for iden...

Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks.

Labeled medical imaging data is scarce and expensive to generate. To achieve generalizable deep learning models large amounts of data are needed. Stan...

Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis.

Machine learning (ML) is ubiquitous in bioinformatics, due to its versatility. One of the most crucial aspects to consider while training a ML model i...

The Identification of Postovulation Infertility with the Measurement of Early Luteal Phase (Peak Day +3) Progesterone Production.

UNLABELLED: This study reports on 632 cycles from 105 women who were using the CREIGHTON MODEL Fertility™ System to avoid pregnancy and had either a s...

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the induction of cancer through epigenetic regulation...

Non-invasive diagnosis of non-alcoholic steatohepatitis and fibrosis with the use of omics and supervised learning: A proof of concept study.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) affects 25-30% of the general population and is characterized by the presence of non-alcoholic f...

Sperm Tail Defects and Abnormal Testicular Blood Flow in a Beagle Dog: A Case Report.

A 5-year-old male Beagle dog produced ejaculates with a high percentage of spermatozoa with abnormal morphology, especially sperm tail defects. Althou...

Antibiotic therapy in patients with high prostate-specific antigen: Is it worth considering? A systematic review.

: To address the question of whether antibiotic therapy can obviate the need for prostate biopsy (PBx) in patients presenting with high prostate-speci...

A Super-Learner Model for Tumor Motion Prediction and Management in Radiation Therapy: Development and Feasibility Evaluation.

In cancer radiation therapy, large tumor motion due to respiration can lead to uncertainties in tumor target delineation and treatment delivery, thus ...

The Use of Transdermal Estrogen in Castrate-resistant, Steroid-refractory Prostate Cancer.

BACKGROUND: Androgen-deprivation therapy is the mainstay of treatment for metastatic prostate cancer. Corticosteroids and estrogens are also useful ag...

Optimizing robot motion for robotic ultrasound-guided radiation therapy.

An important aspect of robotic radiation therapy is active compensation of target motion. Recently, ultrasound has been proposed to obtain real-time v...

Efficacy and safety of degarelix in patients with prostate cancer: Results from a phase III study in China.

OBJECTIVE: To establish non-inferiority of gonadotropin-releasing hormone degarelix compared with goserelin in suppressing and maintaining castrate te...