A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patients.

Background: Haemorrhage transformation (HT) is a serious complication of intravenous thrombolysis (IVT) in acute ischaemic stroke (AIS). Accurate and timely prediction of the risk of HT before IVT may change the treatment decision and improve clinical prognosis. We aimed to develop a deep learning method for predicting HT after IVT for AIS using noncontrast computed tomography (NCCT) images.

Cell-therapy for Parkinson's disease: a systematic review and meta-analysis.

Background: Cell-based strategies focusing on replacement or protection of dopaminergic neurons have been considered as a potential approach to treat Parkinson's disease (PD) for decades. However, despite promising preclinical results, clinical trials on cell-therapy for PD reported mixed outcomes and a thorough synthesis of these findings is lacking. We performed a systematic review and meta-analysis to evaluate cell-therapy for PD patients.

Prediction of Joint Angles Based on Human Lower Limb Surface Electromyography.

Wearable exoskeletons can help people with mobility impairments by improving their rehabilitation. As electromyography (EMG) signals occur before movement, they can be used as input signals for the exoskeletons to predict the body's movement intention. In this paper, the OpenSim software is used to determine the muscle sites to be measured, i.

Therapeutic effect of mesenchymal stem cells in rats with intracerebral hemorrhage: reduced apoptosis and enhanced neuroprotection.

Stem cell transplantation has been used to improve neural function in intracerebral hemorrhage (ICH). However, reports on bone marrow-derived mesenchymal stem cell (MSC) transplantation in ICH are limited. We aimed to explore the therapeutic effect and related mechanisms by transplantation of MSCs in rats with ICH.