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Performance of machine learning algorithms for lung cancer prediction: a comparative approach.

Scientific reports
Due to the excessive growth of PM 2.5 in aerosol, the cases of lung cancer are increasing rapidly and are most severe among other types as the highest mortality rate. In most of the cases, lung cancer is detected with least symptoms at its later stag...

A Deep Learning Approach to Predict Recanalization First-Pass Effect following Mechanical Thrombectomy in Patients with Acute Ischemic Stroke.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Following endovascular thrombectomy in patients with large-vessel occlusion stroke, successful recanalization from 1 attempt, known as the first-pass effect, has correlated favorably with long-term outcomes. Pretreatment imagi...

Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Tumor segmentation is essential in surgical and treatment planning and response assessment and monitoring in pediatric brain tumors, the leading cause of cancer-related death among children. However, manual segmentation is tim...

MCAS-GP: Deep Learning-Empowered Middle Cerebral Artery Segmentation and Gate Proposition.

IEEE/ACM transactions on computational biology and bioinformatics
With the fast development of AI technologies, deep learning is widely applied for biomedical data analytics and digital healthcare. However, there remain gaps between AI-aided diagnosis and real-world healthcare demands. For example, hemodynamic para...

A Parkinson's Auxiliary Diagnosis Algorithm Based on a Hyperparameter Optimization Method of Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Parkinson's disease is a common mental disease in the world, especially in the middle-aged and elderly groups. Today, clinical diagnosis is the main diagnostic method of Parkinson's disease, but the diagnosis results are not ideal, especially in the ...

Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data int...

Human-Robot Collaboration With a Corrective Shared Controlled Robot in a Sanding Task.

Human factors
OBJECTIVE: Physical and cognitive workloads and performance were studied for a corrective shared control (CSC) human-robot collaborative (HRC) sanding task.

Deep learning MR reconstruction in knees and ankles in children and young adults. Is it ready for clinical use?

Skeletal radiology
OBJECTIVE: To evaluate the diagnostic performance and image quality of accelerated Turbo Spin Echo sequences using deep-learning (DL) reconstructions compared to conventional sequences in knee and ankle MRIs of children and young adults.

Automated 3D Cobb Angle Measurement Using U-Net in CT Images of Preoperative Scoliosis Patients.

Journal of imaging informatics in medicine
To propose a deep learning framework "SpineCurve-net" for automated measuring the 3D Cobb angles from computed tomography (CT) images of presurgical scoliosis patients. A total of 116 scoliosis patients were analyzed, divided into a training set of 8...

Infrared spectroscopy coupled with machine learning algorithms for predicting the detailed milk mineral profile in dairy cattle.

Food chemistry
Milk minerals are not only essential components for human health, but they can be informative for milk quality and cow's health. Herein, we investigated the feasibility of Fourier Transformed mid Infrared (FTIR) spectroscopy for the prediction of a d...