A survey on explainable artificial intelligence (xai): Toward medical xai
Recently, artificial intelligence and machine learning in general have demonstrated
remarkable performances in many tasks, from image processing to natural language …
remarkable performances in many tasks, from image processing to natural language …
Deep learning–derived high-level neuroimaging features predict clinical outcomes for large vessel occlusion
Background and Purpose—For patients with large vessel occlusion, neuroimaging
biomarkers that evaluate the changes in brain tissue are important for determining the …
biomarkers that evaluate the changes in brain tissue are important for determining the …
U-net supported segmentation of ischemic-stroke-lesion from brain MRI slices
The brain abnormality is one of the major sicknesses in human's health and the untreated
brain defect will cause major illness. Ischemic stroke is one of the major medical …
brain defect will cause major illness. Ischemic stroke is one of the major medical …
[HTML][HTML] FeMA: Feature matching auto-encoder for predicting ischaemic stroke evolution and treatment outcome
Although, predicting ischaemic stroke evolution and treatment outcome provide important
information one step towards individual treatment planning, classifying functional outcome …
information one step towards individual treatment planning, classifying functional outcome …
Predicting clinical outcome in acute ischemic stroke using parallel multi-parametric feature embedded Siamese network
Stroke is the second leading cause of death and disability worldwide, with ischemic stroke
as the most common type. The preferred diagnostic procedure at the acute stage is the …
as the most common type. The preferred diagnostic procedure at the acute stage is the …
EXplainable Artificial Intelligence (XAI)–From Theory to Methods and Applications
Intelligent applications supported by Machine Learning have achieved remarkable
performance rates for a wide range of tasks in many domains. However, understanding why …
performance rates for a wide range of tasks in many domains. However, understanding why …
Tissue outcome prediction in hyperacute ischemic stroke: Comparison of machine learning models
Machine Learning (ML) has been proposed for tissue fate prediction after acute ischemic
stroke (AIS), with the aim to help treatment decision and patient management. We compared …
stroke (AIS), with the aim to help treatment decision and patient management. We compared …
Prediction of thrombectomy functional outcomes using multimodal data
Recent randomised clinical trials have shown that patients with ischaemic stroke due to
occlusion of a large intracranial blood vessel benefit from endovascular thrombectomy …
occlusion of a large intracranial blood vessel benefit from endovascular thrombectomy …
Comparison of classification methods for tissue outcome after ischaemic stroke
In acute ischaemic stroke, identifying brain tissue at high risk of infarction is important for
clinical decision‐making. This tissue may be identified with suitable classification methods …
clinical decision‐making. This tissue may be identified with suitable classification methods …
Predicting clinical outcome of stroke patients with tractographic feature
PY Kao, JW Chen, BS Manjunath - … Stroke and Traumatic Brain Injuries: 5th …, 2020 - Springer
The volume of stroke lesion is the gold standard for predicting the clinical outcome of stroke
patients. However, the presence of stroke lesion may cause neural disruptions to other brain …
patients. However, the presence of stroke lesion may cause neural disruptions to other brain …