Strokes

Classification of pulmonary sounds through deep learning for the diagnosis of interstitial lung diseases secondary to connective tissue diseases.

Early diagnosis of interstitial lung diseases secondary to connective tissue diseases is critical for the treatment and survival of patients. The symptoms, like dry cough and dyspnea, appear late in the clinical history and are not specific, moreover, the current approach to confirm the diagnosis of interstitial lung disease is based on high resolution computer tomography. However, computer tomogr...

A deep learning and docking simulation-based virtual screening strategy enables the rapid identification of HIF-1α pathway activators from a marine natural product database.

Artificial Intelligence is hailed as a cutting-edge technology for accelerating drug discovery efforts, and our goal was to validate its potential in predicting pharmacological inhibitors of EGLN1 using a deep learning-based architecture, one of its subsidiaries. Egl nine homolog 1 (EGLN1) inhibition prevents poly ubiquitination-mediated proteosomal destruction HIF-1α. The pharmacological interven...

Deep learning prediction of motor performance in stroke individuals using neuroimaging data.

The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical asse...

Radiologist Worklist Reprioritization Using Artificial Intelligence: Impact on Report Turnaround Times for CTPA Examinations Positive for Acute Pulmonary Embolism.

In patients with acute pulmonary embolism (PE), timely intervention (e.g., initiation of anticoagulation) is critical for optimizing clinical outcome...

A Hybrid Stacked CNN and Residual Feedback GMDH-LSTM Deep Learning Model for Stroke Prediction Applied on Mobile AI Smart Hospital Platform.

Artificial intelligence (AI) techniques for intelligent mobile computing in healthcare has opened up new opportunities in healthcare systems. Combinin...

A fuzzy logic-based approach for groundwater vulnerability assessment.

Groundwater vulnerability assessment systems have been developed to protect groundwater resources. The DRASTIC model calculates the vulnerability inde...

Deep Learning-based Assessment of Internal Carotid Artery Anatomy to Predict Difficult Intracranial Access in Endovascular Recanalization of Acute Ischemic Stroke.

BACKGROUND: Endovascular thrombectomy (EVT) duration is an important predictor for neurological outcome. Recently it was shown that an angle of ≤ 90° ...

Ultrafast MRI using deep learning echoplanar imaging for a comprehensive assessment of acute ischemic stroke.

OBJECTIVES: Acute ischemic stroke (AIS) is an emergency requiring both fast and informative MR sequences. We aimed to assess the performance of an art...

Using Deep-Learning-Based Artificial Intelligence Technique to Automatically Evaluate the Collateral Status of Multiphase CTA in Acute Ischemic Stroke.

BACKGROUND: Collateral status is an important predictor for the outcome of acute ischemic stroke with large vessel occlusion. Multiphase computed-tomo...

Effects of Upper Limb Robot-Assisted Rehabilitation Compared with Conventional Therapy in Patients with Stroke: Preliminary Results on a Daily Task Assessed Using Motion Analysis.

Robotic rehabilitation of the upper limb has demonstrated promising results in terms of the improvement of arm function in post-stroke patients. The c...

Big Data in Stroke: How to Use Big Data to Make the Next Management Decision.

The last decade has seen significant advances in the accumulation of medical data, the computational techniques to analyze that data, and correspondin...

External Validation of an Artificial Intelligence Device for Intracranial Hemorrhage Detection.

BACKGROUND: Artificial intelligence applications have gained traction in the field of cerebrovascular disease by assisting in the triage, classificati...

Analyzing the Relationship among Social Capital, Dynamic Capability, and Farmers' Cooperative Performance Using Lightweight Deep Learning Model: A Case Study of Liaoning Province.

The purpose of this study is to understand the relationship between social capital and the performance of Farmers' Cooperatives (Cooperatives) and exp...

SAN-Net: Learning generalization to unseen sites for stroke lesion segmentation with self-adaptive normalization.

There are considerable interests in automatic stroke lesion segmentation on magnetic resonance (MR) images in the medical imaging field, as stroke is ...

Automated in-depth cerebral arterial labelling using cerebrovascular vasculature reframing and deep neural networks.

Identifying the cerebral arterial branches is essential for undertaking a computational approach to cerebrovascular imaging. However, the complexity a...

Dyspnea Severity Assessment Based on Vocalization Behavior with Deep Learning on the Telephone.

In this paper, a system to assess dyspnea with the mMRC scale, on the phone, via deep learning, is proposed. The method is based on modeling the spont...

Evaluating Fluency in Aphasia: Fluency Scales, Trichotomous Judgements, or Machine Learning.

BACKGROUND: Speech-language pathologists (SLPs) and other clinicians often use aphasia batteries, such as the Western Aphasia Battery-Revised (WAB-R),...

Effects of Timed Frontal Plane Pelvic Moments During Overground Walking With a Mobile TPAD System.

Robotic gait training may improve overground ambulation for individuals with poor control over pelvic motion. However, there is a need for an overgrou...

The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke.

BACKGROUND: Robots can generate rich kinematic datasets that have the potential to provide far more insight into impairments than standard clinical or...

Electrocardiogram Detection of Pulmonary Hypertension Using Deep Learning.

BACKGROUND: Pulmonary hypertension (PH) is life-threatening, and often diagnosed late in its course. We aimed to evaluate if a deep learning approach ...