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Niazi, Muhammad Khalid Khan

One or more keywords matched the following properties of Niazi, Muhammad Khalid Khan

Property	Value
keywords	Digital pathology, deep learning, machine learning, computed aided diagnosis, image analysis
keywords	Computational pathology, deep learning

One or more keywords matched the following items that are connected to Niazi, Muhammad Khalid Khan

Item Type	Name
Concept	Artificial Intelligence
Academic Article	Lung necrosis and neutrophils reflect common pathways of susceptibility to Mycobacterium tuberculosis in genetically diverse, immune-competent mice.
Academic Article	Histopathological image analysis for centroblasts classification through dimensionality reduction approaches.
Academic Article	Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning.
Academic Article	DeepFocus: Detection of out-of-focus regions in whole slide digital images using deep learning.
Academic Article	Digital pathology and artificial intelligence.
Award or Honor Receipt	Best paper award
Academic Article	Ros-NET: A deep convolutional neural network for automatic identification of rosacea lesions.
Academic Article	OtoMatch: Content-based eardrum image retrieval using deep learning.
Academic Article	Semantic segmentation to identify bladder layers from H&E Images.
Academic Article	Velocity-image model for online signature verification.
Academic Article	Automatic discovery of clinically interpretable imaging biomarkers for Mycobacterium tuberculosis supersusceptibility using deep learning.
Grant	Development of machine learning algorithms to predict difficult airway management
Grant	A Deep Learning Approach to Measure the Histological Similarity Between Real and Regenerated Tissue Sections
Grant	Improving the Diagnosis of Obstructive Sleep Apnea Through Deep Learning.
Academic Article	Deep learning predicts gene expression as an intermediate data modality to identify susceptibility patterns in Mycobacterium tuberculosis infected Diversity Outbred mice.
Academic Article	Identification of difficult to intubate patients from frontal face images using an ensemble of deep learning models.
Academic Article	Contrastive Multiple Instance Learning: An Unsupervised Framework for Learning Slide-Level Representations of Whole Slide Histopathology Images without Labels.
Academic Article	Attention2majority: Weak multiple instance learning for regenerative kidney grading on whole slide images.

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Artificial Intelligence
Deep
Learning Machine
Learning