Orthopedics

Deep Learning Approach for Anterior Cruciate Ligament Lesion Detection: Evaluation of Diagnostic Performance Using Arthroscopy as the Reference Standard.

BACKGROUND: MRI is the most commonly used imaging method for diagnosing anterior cruciate ligament (ACL) injuries. However, the interpretation of knee MRI is time-intensive and depends on the clinical experience of the reader. An automated detection system based on a deep-learning algorithm may improve interpretation time and reliability.

Multi-task multi-modal learning for joint diagnosis and prognosis of human cancers.

With the tremendous development of artificial intelligence, many machine learning algorithms have been applied to the diagnosis of human cancers. Recently, rather than predicting categorical variables (e.g., stages and subtypes) as in cancer diagnosis, several prognosis prediction models basing on patients' survival information have been adopted to estimate the clinical outcome of cancer patients....

An enhanced machine learning tool for cis-eQTL mapping with regularization and confounder adjustments.

Many expression quantitative trait loci (eQTL) studies have been conducted to investigate the biological effects of variants in gene regulation. Howev...

An efficient end-to-end CNN for segmentation of bone surfaces from ultrasound.

The application of ultrasound (US) imaging in orthopedic surgery has always been a research direction. However, the various problems of US imaging hin...

A machine learning approach for mortality prediction only using non-invasive parameters.

At present, the traditional scoring methods generally utilize laboratory measurements to predict mortality. It results in difficulties of early mortal...

Antifungal activity of selected volatile essential oils against sp.

Phytopathogenic fungi have been responsible for considerable economic losses in vineyards, and therefore, more attention should be paid to the develop...

Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks.

Bone scintigraphy is accepted as an effective diagnostic tool for whole-body examination of bone metastasis. However, the manual analysis of bone scin...

Bone-Inspired Bending Soft Robot.

Bending soft robots must be structured and predictable to be used in applications such as a grasping hand. We developed soft robot fingers with embedd...

Toward Task Autonomy in Robotic Cardiac Ablation: Learning-Based Kinematic Control of Soft Tendon-Driven Catheters.

The goal of this study was to propose and validate a control framework with level-2 autonomy (task autonomy) for the control of flexible ablation cath...

Bone shadow segmentation from ultrasound data for orthopedic surgery using GAN.

PURPOSE: Real-time, two (2D) and three-dimensional (3D) ultrasound (US) has been investigated as a potential alternative to fluoroscopy imaging in var...

DISC: a highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.

Dropouts distort gene expression and misclassify cell types in single-cell transcriptome. Although imputation may improve gene expression and downstre...

Automatic Midline Identification in Transverse 2-D Ultrasound Images of the Spine.

Effective epidural needle placement and injection involves accurate identification of the midline of the spine. Ultrasound, as a safe pre-procedural i...

Use of deep learning to detect cardiomegaly on thoracic radiographs in dogs.

The purpose of this study was to develop a computer-aided detection (CAD) device based on convolutional neural networks (CNNs) to detect cardiomegaly ...

A Self-Powered Angle Sensor at Nanoradian-Resolution for Robotic Arms and Personalized Medicare.

As the dominant component for precise motion measurement, angle sensors play a vital role in robotics, machine control, and personalized rehabilitatio...

Automated histologic diagnosis of CNS tumors with machine learning.

The discovery of a new mass involving the brain or spine typically prompts referral to a neurosurgeon to consider biopsy or surgical resection. Intrao...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. Howe...

A Retrospective Comparison of Deep Learning to Manual Annotations for Optic Disc and Optic Cup Segmentation in Fundus Photographs.

PURPOSE: Optic disc (OD) and optic cup (OC) segmentation are fundamental for fundus image analysis. Manual annotation is time consuming, expensive, an...

Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative.

Background The methods for assessing knee osteoarthritis (OA) do not provide enough comprehensive information to make robust and accurate outcome pred...

Characterizing forearm muscle activity in young adults during dynamic wrist flexion-extension movement using a wrist robot.

Current research suggests that the wrist extensor muscles function as the primary stabilizers of the wrist-joint complex. However, most investigations...

Serum adipokines/related inflammatory factors and ratios as predictors of infrapatellar fat pad volume in osteoarthritis: Applying comprehensive machine learning approaches.

OBJECTIVE: The infrapatellar fat pad (IPFP) has been associated with knee osteoarthritis onset and progression. This study uses machine learning (ML) ...