Menopause

Analysis of Gastrointestinal Acoustic Activity Using Deep Neural Networks.

Automated bowel sound (BS) analysis methods were already well developed by the early 2000s. Accuracy of ~90% had been achieved by several teams using various analytical approaches. Clinical research on BS had revealed their high potential in the non-invasive investigation of irritable bowel syndrome to study gastrointestinal motility and in a surgical setting. This article proposes a novel methodo...

Generation of Vertebra Micro-CT-like Image from MDCT: A Deep-Learning-Based Image Enhancement Approach.

This paper proposes a deep-learning-based image enhancement approach that can generate high-resolution micro-CT-like images from multidetector computed tomography (MDCT). A total of 12,500 MDCT and micro-CT image pairs were obtained from 25 vertebral specimens. Then, a pix2pixHD model was trained and evaluated using the structural similarity index measure (SSIM) and Fréchet inception distance (FID...

Integration of Deep Learning Radiomics and Counts of Circulating Tumor Cells Improves Prediction of Outcomes of Early Stage NSCLC Patients Treated With Stereotactic Body Radiation Therapy.

PURPOSE: We develop a deep learning (DL) radiomics model and integrate it with circulating tumor cell (CTC) counts as a clinically useful prognostic m...

Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.

fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceive a baby successfully. Nevertheless, IVF-ET does n...

Graphene oxide enhanced the endocrine disrupting effects of bisphenol A in adult male zebrafish: Integrated deep learning and metabolomics studies.

In our previous studies, it was found that graphene oxide (GO) reduced the endocrine disruption of bisphenol A (BPA) in zebrafish embryo and larvae, b...

Enhanced precision of real-time control photothermal therapy using cost-effective infrared sensor array and artificial neural network.

Photothermal therapy (PTT) requires tight thermal dose control to achieve tumor ablation with minimal thermal injury on surrounding healthy tissues. I...

Applications of Machine Learning in Bone and Mineral Research.

In this unprecedented era of the overwhelming volume of medical data, machine learning can be a promising tool that may shed light on an individualize...

Should we replace radiologists with deep learning? Pigeons, error and trust in medical AI.

The sudden rise in the ability of machine learning methodology, such as deep neural networks, to identify and predict with great accuracy instances of...

Real-Time Detection of Non-Stationary Objects Using Intensity Data in Automotive LiDAR SLAM.

This article aims at demonstrating the feasibility of modern deep learning techniques for the real-time detection of non-stationary objects in point c...

Application of Medical Imaging Based on Deep Learning in the Treatment of Lumbar Degenerative Diseases and Osteoporosis with Bone Cement Screws.

OBJECTIVE: To explore the application value of magnetic resonance spectroscopy (MRS) and GSI-energy spectrum electronic computed tomography (CT) medic...

DMFMDA: Prediction of Microbe-Disease Associations Based on Deep Matrix Factorization Using Bayesian Personalized Ranking.

Identifying the microbe-disease associations is conducive to understanding the pathogenesis of disease from the perspective of microbe. In this paper,...

The effects of as a libido booster and sexual enhancer on the reproductive system of male rats.

BACKGROUND AND AIM: Alongside the advancement of various modern treatments, attention has recently been focused on finding alternative infertility tre...

Automated bone mineral density prediction and fracture risk assessment using plain radiographs via deep learning.

Dual-energy X-ray absorptiometry (DXA) is underutilized to measure bone mineral density (BMD) and evaluate fracture risk. We present an automated tool...

Repurposing non-oncology small-molecule drugs to improve cancer therapy: Current situation and future directions.

Drug repurposing or repositioning has been well-known to refer to the therapeutic applications of a drug for another indication other than it was orig...

Combining computed tomography and biologically effective dose in radiomics and deep learning improves prediction of tumor response to robotic lung stereotactic body radiation therapy.

PURPOSE: The aim of this study is to improve the performance of machine learning (ML) models in predicting response of non-small cell lung cancer (NSC...

Automated description of the mandible shape by deep learning.

PURPOSE: The shape of the mandible has been analyzed in a variety of fields, whether to diagnose conditions like osteoporosis or osteomyelitis, in for...

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis.

The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes i...

Deep learning takes the pain out of back breaking work - Automatic vertebral segmentation and attenuation measurement for osteoporosis.

BACKGROUND: Osteoporosis is an underdiagnosed and undertreated disease worldwide. Recent studies have highlighted the use of simple vertebral trabecul...

Effect of hybrid drying on the quality attributes of formulated instant banana-milk powders and shakes during storage.

The present research aimed to evaluate the effect of microwave-assisted conventional drying (hybrid drying) on the physico-chemical and functional cha...

Effect of Patient Clinical Variables in Osteoporosis Classification Using Hip X-rays in Deep Learning Analysis.

: A few deep learning studies have reported that combining image features with patient variables enhanced identification accuracy compared with image-...