Search Results for author: Mingli Zhang

Found 6 papers, 0 papers with code

Modeling of Textures to Predict Immune Cell Status and Survival of Brain Tumour Patients

no code implementations4 Jun 2022 Ahmad Chaddad, Mingli Zhang, Lama Hassan, Tamim Niazi

Combined the immune markers with DRFs and clinical variables, Kaplan-Meier estimator and Log-rank test achieved the most significant difference between predicted groups of patients (short-term versus long-term survival) with p\,=\, 4. 31$\times$10$^{-7}$ compared to p\,=\, 0. 03 for Immune cell markers, p\,=\, 0. 07 for clinical variables , and p\,=\, 1. 45$\times$10$^{-5}$ for DRFs.

A Generic Knowledge Based Medical Diagnosis Expert System

no code implementations9 Oct 2021 Xin Huang, Xuejiao Tang, Wenbin Zhang, Shichao Pei, Ji Zhang, Mingli Zhang, Zhen Liu, Ruijun Chen, Yiyi Huang

The proposed disease diagnosis system also uses a graphical user interface (GUI) to facilitate users to interact with the expert system.

Medical Diagnosis

LSTM Based Sentiment Analysis for Cryptocurrency Prediction

no code implementations27 Mar 2021 Xin Huang, Wenbin Zhang, Xuejiao Tang, Mingli Zhang, Jayachander Surbiryala, Vasileios Iosifidis, Zhen Liu, Ji Zhang

Recent studies in big data analytics and natural language processing develop automatic techniques in analyzing sentiment in the social media information.

Natural Language Processing Sentiment Analysis

A Data-driven Human Responsibility Management System

no code implementations6 Dec 2020 Xuejiao Tang, Jiong Qiu, Ruijun Chen, Wenbin Zhang, Vasileios Iosifidis, Zhen Liu, Wei Meng, Mingli Zhang, Ji Zhang

An ideal safe workplace is described as a place where staffs fulfill responsibilities in a well-organized order, potential hazardous events are being monitored in real-time, as well as the number of accidents and relevant damages are minimized.

Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma

no code implementations15 Nov 2019 Ahmad Chaddad, Saima Rathore, Mingli Zhang, Christian Desrosiers, Tamim Niazi

This paper proposes to use deep radiomic features (DRFs) from a convolutional neural network (CNN) to model fine-grained texture signatures in the radiomic analysis of recurrent glioblastoma (rGBM).

General Classification

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