Menopause

Promoter prediction in nannochloropsis based on densely connected convolutional neural networks.

Promoter is a key DNA element located near the transcription start site, which regulates gene transcription by binding RNA polymerase. Thus, the identification of promoters is an important research field in synthetic biology. Nannochloropsis is an important unicellular industrial oleaginous microalgae, and at present, some studies have identified some promoters with specific functions by biologica...

Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs using an Adaptation of the Genant Semiquantitative Criteria.

RATIONALE AND OBJECTIVES: Osteoporosis affects 9% of individuals over 50 in the United States and 200 million women globally. Spinal osteoporotic compression fractures (OCFs), an osteoporosis biomarker, are often incidental and under-reported. Accurate automated opportunistic OCF screening can increase the diagnosis rate and ensure adequate treatment. We aimed to develop a deep learning classifier...

Impact of the training loss in deep learning-based CT reconstruction of bone microarchitecture.

PURPOSE: Computed tomography (CT) is a technique of choice to image bone structure at different scales. Methods to enhance the quality of degraded rec...

[Artificial intelligence (AI) in radiology? : Do we need as many radiologists in the future?].

We are in the middle of a digital revolution in medicine. This raises the question of whether subjects such as radiology, which is superficially conce...

Implicitly perturbed Hamiltonian as a class of versatile and general-purpose molecular representations for machine learning.

Unraveling challenging problems by machine learning has recently become a hot topic in many scientific disciplines. For developing rigorous machine-le...

ACPNet: A Deep Learning Network to Identify Anticancer Peptides by Hybrid Sequence Information.

Cancer is one of the most dangerous threats to human health. One of the issues is drug resistance action, which leads to side effects after drug treat...

A machine learning-based on-demand sweat glucose reporting platform.

Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and altering carbohydrate metabolism. It is a leading cause ...

An AI-based Prediction Model for Drug-drug Interactions in Osteoporosis and Paget's Diseases from SMILES.

The skeleton is one of the most important organs in the human body in assisting our motion and activities; however, bone density attenuates gradually ...

Artificial intelligence approaches to the determinants of women's vaginal dryness using general hospital data.

The aim of this study is to analyse the determinants of women's vaginal dryness using machine learning. Data came from Korea University Anam Hospital ...

Computational identification of 4-carboxyglutamate sites to supplement physiological studies using deep learning.

In biological systems, Glutamic acid is a crucial amino acid which is used in protein biosynthesis. Carboxylation of glutamic acid is a significant po...

Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis.

Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third of UC patients show primary non-response (PNR) to...

Opportunistic Osteoporosis Screening Using Chest Radiographs With Deep Learning: Development and External Validation With a Cohort Dataset.

Osteoporosis is a common, but silent disease until it is complicated by fractures that are associated with morbidity and mortality. Over the past few ...

Using a convolutional neural network for classification of squamous and non-squamous non-small cell lung cancer based on diagnostic histopathology HES images.

Histological stratification in metastatic non-small cell lung cancer (NSCLC) is essential to properly guide therapy. Morphological evaluation remains ...

A Pan-Cancer Analysis of Predictive Methylation Signatures of Response to Cancer Immunotherapy.

Recently, tumor immunotherapy based on immune checkpoint inhibitors (ICI) has been introduced and widely adopted for various tumor types. Nevertheless...

Personalized Cell Therapy for Patients with Peripheral Arterial Diseases in the Context of Genetic Alterations: Artificial Intelligence-Based Responder and Non-Responder Prediction.

Stem/progenitor cell transplantation is a potential novel therapeutic strategy to induce angiogenesis in ischemic tissue, which can prevent major ampu...

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 ...

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 compute...

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...

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...