Arthritis

A fully automatic target detection and quantification strategy based on object detection convolutional neural network YOLOv3 for one-step X-ray image grading.

Methods for automatic image analysis are demanded for dealing with the explosively increased imaging data in clinics. Osteoarthritis (OA) is a typical disease diagnosed based on X-ray imaging. Herein, we propose a novel modeling strategy based on YOLO version 3 (YOLOv3) for automatic simultaneous localization of knee joints and quantification of radiographic knee OA. As an advanced deep convolutio...

Prediction of coronary heart disease in gout patients using machine learning models.

Growing evidence shows that there is an increased risk of cardiovascular diseases among gout patients, especially coronary heart disease (CHD). Screening for CHD in gout patients based on simple clinical factors is still challenging. Here we aim to build a diagnostic model based on machine learning so as to avoid missed diagnoses or over exaggerated examinations as much as possible. Over 300 patie...

Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models.

Background Radiomics is the extraction of predefined mathematic features from medical images for the prediction of variables of clinical interest. Whi...

Automatic assessment of knee osteoarthritis severity in portable devices based on deep learning.

BACKGROUND: For knee osteoarthritis, the commonly used radiology severity criteria Kellgren-Lawrence lead to variability among surgeons. Most existing...

Artificial intelligence in cancer research and precision medicine: Applications, limitations and priorities to drive transformation in the delivery of equitable and unbiased care.

Artificial intelligence (AI) has experienced explosive growth in oncology and related specialties in recent years. The improved expertise in data capt...

Preliminary outcomes of kinematically aligned robot-assisted total knee arthroplasty with patient-specific cartilage thickness measurement.

This study aimed to assess the preliminary outcomes of kinematically aligned robot-assisted total knee arthroplasty (TKA) with patient-specific cartil...

Radiographic findings involved in knee osteoarthritis progression are associated with pain symptom frequency and baseline disease severity: a population-level analysis using deep learning.

PURPOSE: To (1) develop a deep-learning (DL) algorithm capable of producing limb-length and knee-alignment measurements, and (2) determine the associa...

A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repair.

INTRODUCTION: The use of biologic adjuvants (orthobiologics) is becoming commonplace in orthopaedic surgery. Among other applications, biologics are o...

Exactech Equinoxe anatomic versus reverse total shoulder arthroplasty for primary osteoarthritis: case controlled comparisons using the machine learning-derived Shoulder Arthroplasty Smart score.

BACKGROUND: The role of reverse total shoulder arthroplasty (rTSA) for glenohumeral osteoarthritis (GHOA) with an intact rotator cuff remains unclear ...

Artificial Intelligence and Deep Learning for Rheumatologists.

Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing field of academic research and commercial applications...

High-resolution knee plain radiography image synthesis using style generative adversarial network adaptive discriminator augmentation.

In this retrospective study, 10,000 anteroposterior (AP) radiography of the knee from a single institution was used to create medical data set that ar...

Deep learning-based automatic-bone-destruction-evaluation system using contextual information from other joints.

BACKGROUND: X-ray images are commonly used to assess the bone destruction of rheumatoid arthritis. The purpose of this study is to propose an automati...

Deep Learning-Based Nuclear Morphometry Reveals an Independent Prognostic Factor in Mantle Cell Lymphoma.

Blastoid/pleomorphic morphology is associated with short survival in mantle cell lymphoma (MCL), but its prognostic value is overridden by Ki-67 in mu...

Using Unsupervised Machine Learning Methods to Cluster Comorbidities in a Population-Based Cohort of Patients With Rheumatoid Arthritis.

OBJECTIVE: To identify clusters of comorbidities in patients with rheumatoid arthritis (RA) using 4 methods and to compare to patients without RA.

Sex Imbalance Produces Biased Deep Learning Models for Knee Osteoarthritis Detection.

Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment.

PURPOSE: Evaluating lower extremity alignment using full-leg plain radiographs is an essential step in diagnosis and treatment of patients with knee o...

Nuclear morphology is a deep learning biomarker of cellular senescence.

Cellular senescence is an important factor in aging and many age-related diseases, but understanding its role in health is challenging due to the lack...

The Artificial Intelligence System for the Generation of Sports Education Guidance Model and Physical Fitness Evaluation Under Deep Learning.

In recent years, China's achievements in artificial intelligence (AI) have attracted the attention of the world, and AI technology has penetrated into...

Design of predictive model to optimize the solubility of Oxaprozin as nonsteroidal anti-inflammatory drug.

These days, many efforts have been made to increase and develop the solubility and bioavailability of novel therapeutic medicines. One of the most bel...

Successful real-world application of an osteoarthritis classification deep-learning model using 9210 knees-An orthopedic surgeon's view.

This study aimed to evaluate the performance of a deep-learning model to evaluate knee osteoarthritis using Kellgren-Lawrence grading in real-life kne...