Obstetrics & Gynecology

Utility of machine learning algorithms in degenerative cervical and lumbar spine disease: a systematic review.

Machine learning is a rapidly evolving field that offers physicians an innovative and comprehensive mechanism to examine various aspects of patient data. Cervical and lumbar degenerative spine disorders are commonly age-related disease processes that can utilize machine learning to improve patient outcomes with careful patient selection and intervention. The aim of this study is to examine the cur...

Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa.

BACKGROUND: Babies born early and/or small for gestational age in Low and Middle-income countries (LMICs) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, advocacy, resources allocation and program evaluation and at an individual level for targeted care. Early prenatal ultrasound examination is not availab...

Uterine Transplantation with Robot-assisted Uterus Retrieval from Living Donor: First Case in Brazil.

OBJECTIVE: To present the first robot-assisted uterus retrieval from a living donor for uterine transplantation in Brazil.

Artificial intelligence in gynecologic cancers: Current status and future challenges - A systematic review.

OBJECTIVE: Over the past years, the application of artificial intelligence (AI) in medicine has increased rapidly, especially in diagnostics, and in t...

Can co-authorship networks be used to predict author research impact? A machine-learning based analysis within the field of degenerative cervical myelopathy research.

INTRODUCTION: Degenerative Cervical Myelopathy (DCM) is a common and disabling condition, with a relatively modest research capacity. In order to acce...

HOX cluster and their cofactors showed an altered expression pattern in eutopic and ectopic endometriosis tissues.

Endometriosis is major gynecological disease that affects over 10% of women worldwide and 30%-50% of these women have pelvic pain, abnormal uterine bl...

Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management.

The study aims to explore the application of international classification of diseases (ICD) coding technology and embedded electronic medical record (...

Malfunction Events in the US FDA MAUDE Database: How Does Robotic Gynecologic Surgery Compare with Other Specialties?

STUDY OBJECTIVE: To review malfunction events (MEs) related to the use of the da Vinci robot reported to the United States Food and Drug Administratio...

Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases.

In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms that resist conventional antibiotic treatment has steadil...

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...

Automatic annotation of cervical vertebrae in videofluoroscopy images via deep learning.

Judging swallowing kinematic impairments via videofluoroscopy represents the gold standard for the detection and evaluation of swallowing disorders. H...

Deep learning to diagnose pouch of Douglas obliteration with ultrasound sliding sign.

OBJECTIVES: Pouch of Douglas (POD) obliteration is a severe consequence of inflammation in the pelvis, often seen in patients with endometriosis. The ...

Ethical impact of suboptimal referrals on delivery of care in radiology department.

The referral is the key source of information that enables radiologists and radiographers to provide quality services. However, the frequency of subop...

Robot-assisted partial cystectomy for bladder endometriosis: dual approach involving cystoscopy and robotic surgery.

Bladder endometriosis accounts for 70%-85% cases of urinary tract endometriosis. A high index of suspicion is needed to diagnose this condition as mos...

Cancer survivorship care and general practice: A qualitative study of roles of general practice team members in Australia.

Primary care providers, including general practice teams (GPTs), are well positioned within the community to integrate cancer survivorship care into o...

Estimating the conditional probability of developing human papilloma virus related oropharyngeal cancer by combining machine learning and inverse Bayesian modelling.

The epidemic increase in the incidence of Human Papilloma Virus (HPV) related Oropharyngeal Squamous Cell Carcinomas (OPSCCs) in several countries wor...

Computational pharmaceutics - A new paradigm of drug delivery.

In recent decades pharmaceutics and drug delivery have become increasingly critical in the pharmaceutical industry due to longer time, higher cost, an...

A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.

Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to ide...

The present and future of intrapartum computerized cardiotocography: role of pattern recognition incorporating single vs. multiple parameters.

Computer assisted cardiotocography holds a great promise in minimizing human errors thereby improving perinatal outcome. Despite exponential growth (M...

Prediction of hand-wrist maturation stages based on cervical vertebrae images using artificial intelligence.

OBJECTIVE: To predict the hand-wrist maturation stages based on the cervical vertebrae (CV) images, and to analyse the accuracy of the proposed algori...