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Advanced Survival Prediction in Head and Neck Cancer Using Hybrid Machine Learning Systems and Radiomics …
Objective: Accurate prognostic stratification of Head-and-Neck-Squamous-Cell-Carcinoma (HNSCC) patients can be an important clinical reference when designing therapeutic strategies. We set to predict 4 outcomes: overall-survival …
Aug. 1, 2021
Prediction of TNM Stage in Head and Neck Cancer Using Hybrid Machine Learning Systems and …
Objective: The tumor, node, metastasis (TNM) staging system enables clinicians to describe the spread of head-and-neck-squamous-cell-carcinoma (HNSCC) cancer in a specific manner to assist with …
Aug. 1, 2021
Drug Amount Prediction in Parkinson’s Disease Using Hybrid Machine Learning Systems and Radiomics Features
Objectives: Parkinson’s Disease (PD) is progressive and heterogeneous. Predicting and personalizing drug amount consistently to treat PD patients holds significant promises to enhance chances of …
Aug. 1, 2021
Multi-Modality Fusion Coupled with Deep Learning for Improved Outcome Prediction in Head and Neck Cancer
Objective: Multi-level multi-modality-fusion-radiomics is a promising technique with potential for improved prognostication of cancer. We aim to use advanced fusion-techniques on PET and CT images …
Aug. 1, 2021
Cognitive Outcome Prediction in Parkinson’s Disease Using Hybrid Machine Learning Systems and Radiomics Features
Objective: Montreal Cognitive Assessment (MoCA) as a rapid nonmotor-screening test assesses different aspects of cognitive dysfunction. Early prediction of these symptoms may facilitate better temporal …
Sept. 1, 2021
Robust identification of Parkinson’s disease subtypes using radiomics and hybrid machine learning
Objectives: It is important to subdivide Parkinson’s disease (PD) into subtypes, enabling potentially earlier disease recognition and tailored treatment strategies. We aimed to identify reproducible …
Dec. 20, 2020
Using deep-learning to predict outcome of patients with Parkinson’s disease
Abstract–There are currently no established disease modifying therapies for PD, and prediction of outcome in PD to power clinical studies is a very important area …
Dec. 22, 2021
Applying multiple feature extraction models on PET images to improve outcome prediction in head and …
Head and neck squamous cell carcinoma (HNSCC) describe a wide range of malignant tumors that spread in or around the nose, mouth, throat, larynx, and …
Dec. 21, 2021
prediction of treatment response in PD, how can we predict the improvement when applying the …
Parkinson’s Disease (PD) is progressive and heterogeneous. Predicting and personalizing response to treatment consistently to treat PD patients holds significant promises to enhance chances of …
Dec. 20, 2021
How Much Can Employment of Attention Map and Fusion Techniques Improve Binary Survival Prediction in …
In this study, multi-level multi-modality-fusion technique is a promising technique with potential for improved prognostication of cancer. We aim to use advanced fusion techniques and …
Dec. 20, 2021
Hybrid Machine Learning Methods and Ensemble Voting for Identification of Parkinson’s Disease Subtypes
Objectives: It is important to subdivide Parkinson’s disease (PD) into specific subtypes, since homogeneous groups of patients are more likely to share genetic and pathological …
Feb. 18, 2021
Longitudinal Clustering Analysis and Prediction of Parkinson’s Disease Progression
Objectives: We aimed to identify distinct disease progression pathways in Parkinson’s disease (PD), making use of clinical and imaging features, towards improved understanding of disease …
May 18, 2021
