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Feature selection and machine learning methods for optimal identification and prediction of subtypes in Parkinson's disease

Computer methods and programs in biomedicine, 2021-07, Vol.206, p.106131-106131, Article 106131

2021

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Deep versus Handcrafted Tensor Radiomics Features: Prediction of Survival in Head and Neck Cancer Using Machine Learning and Fusion Techniques

Diagnostics (Basel), 2023-05, Vol.13 (10), p.1696

2023

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Prediction of Cognitive Decline in Parkinson's Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems

Diagnostics (Basel), 2023-05, Vol.13 (10), p.1691

2023

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Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease

Computers in biology and medicine, 2019-08, Vol.111, p.103347-103347, Article 103347

2019

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Machine learning methods for optimal prediction of motor outcome in Parkinson’s disease

Physica medica, 2020-01, Vol.69, p.233-240

2020

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Fusion-based tensor radiomics using reproducible features: Application to survival prediction in head and neck cancer

Computer methods and programs in biomedicine, 2023-10, Vol.240, p.107714-107714, Article 107714

2023

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Control rod drop-time reduction in typical swimming pool research reactors

Progress in nuclear energy (New series), 2018-07, Vol.106, p.146-152

2018

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Robust identification of Parkinson's disease subtypes using radiomics and hybrid machine learning

Computers in biology and medicine, 2021-02, Vol.129, p.104142-104142, Article 104142

2021

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Application of novel hybrid machine learning systems and radiomics features for non-motor outcome prediction in Parkinson’s disease

Physics in medicine & biology, 2023-02, Vol.68 (3), p.35004

2023

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Prediction of drug amount in Parkinson's disease using hybrid machine learning systems and radiomics features

International journal of imaging systems and technology, 2023-07, Vol.33 (4), p.1437-1449

2023

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Longitudinal clustering analysis and prediction of Parkinson's disease progression using radiomics and hybrid machine learning

Quantitative imaging in medicine and surgery, 2022-02, Vol.12 (2), p.906-919

2022

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Prediction of Parkinson’s disease pathogenic variants using hybrid Machine learning systems and radiomic features

Physica medica, 2023-09, Vol.113, p.102647-102647, Article 102647

2023

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The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights

Radiology, 2024-02, Vol.310 (2), p.e231319

2024

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Tensor radiomics: paradigm for systematic incorporation of multi-flavoured radiomics features

Quantitative imaging in medicine and surgery, 2023-12, Vol.13 (12), p.7680-7694

2023

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Epidemiology of pemphigus in south‐western Iran: A 10‐year retrospective study (1991–2000)

International journal of dermatology, 2006-02, Vol.45 (2), p.103-105

2006

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Fusion-Based Automated Segmentation in Head and Neck Cancer via Advance Deep Learning Techniques

Head and Neck Tumor Segmentation and Outcome Prediction, 2023, Vol.13626, p.70-76

2023

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Comparative study of the efficacy of oral ketoconazole with intra-lesional meglumine antimoniate (Glucantime) for the treatment of cutaneous leishmaniasis

The Journal of dermatological treatment, 2001, Vol.12 (3), p.159-162

Salmanpour, F Handjani, M K Nouhpisheh, R

2001

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Fusion-Based Head and Neck Tumor Segmentation and Survival Prediction Using Robust Deep Learning Techniques and Advanced Hybrid Machine Learning Systems

Head and Neck Tumor Segmentation and Outcome Prediction, 2022, Vol.13209, p.211-223

2022

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Comparison of sympathetic skin response between palmar hyperhidrotic and normal subjects

Electromyography and clinical neurophysiology, 2004-01, Vol.44 (1), p.51

2004

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FC25 IL-18 promoter variations at position -607 C/A is associated with individuals susceptibility to Basal Cell Carcinoma

Melanoma research, 2010-06, Vol.20, p.e40-e41

2010

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P50 TGF-β-509 C allele and CC genotype is associated with susceptibility to basal cell carcinoma

Melanoma research, 2010-06, Vol.20, p.e65

2010

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A double-blind randomized clinical trial of a topical herbal extract (Z-HE) vs. systemic meglumine antimoniate for the treatment of cutaneous leishmaniasis in Iran

International journal of dermatology, 1999-08, Vol.38 (8), p.610-612

1999

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Erysipeloid leishmaniasis : an unusual clinical presentation

EJD. European journal of dermatology, 1999-09, Vol.9 (6), p.458-459

1999

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Using deep-learning to predict outcome of patients with Parkinson's disease

2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC), 2018, p.1-4

2018

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Machine Learning Methods for Optimal Prediction of Outcome in Parkinson's Disease

2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC), 2018, p.1-5

2018

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Feature selection and machine learning methods for optimal identification and prediction of subtypes in Parkinson's disease

Deep versus Handcrafted Tensor Radiomics Features: Prediction of Survival in Head and Neck Cancer Using Machine Learning and Fusion Techniques

Prediction of Cognitive Decline in Parkinson's Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems

Optimized machine learning methods for prediction of cognitive outcome in Parkinson's disease

Machine learning methods for optimal prediction of motor outcome in Parkinson’s disease

Fusion-based tensor radiomics using reproducible features: Application to survival prediction in head and neck cancer

Control rod drop-time reduction in typical swimming pool research reactors

Robust identification of Parkinson's disease subtypes using radiomics and hybrid machine learning

Application of novel hybrid machine learning systems and radiomics features for non-motor outcome prediction in Parkinson’s disease

Prediction of drug amount in Parkinson's disease using hybrid machine learning systems and radiomics features

Longitudinal clustering analysis and prediction of Parkinson's disease progression using radiomics and hybrid machine learning

Prediction of Parkinson’s disease pathogenic variants using hybrid Machine learning systems and radiomic features

The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights

Tensor radiomics: paradigm for systematic incorporation of multi-flavoured radiomics features

Epidemiology of pemphigus in south‐western Iran: A 10‐year retrospective study (1991–2000)

Fusion-Based Automated Segmentation in Head and Neck Cancer via Advance Deep Learning Techniques

Comparative study of the efficacy of oral ketoconazole with intra-lesional meglumine antimoniate (Glucantime) for the treatment of cutaneous leishmaniasis

Fusion-Based Head and Neck Tumor Segmentation and Survival Prediction Using Robust Deep Learning Techniques and Advanced Hybrid Machine Learning Systems

Comparison of sympathetic skin response between palmar hyperhidrotic and normal subjects

FC25 IL-18 promoter variations at position -607 C/A is associated with individuals susceptibility to Basal Cell Carcinoma

P50 TGF-β-509 C allele and CC genotype is associated with susceptibility to basal cell carcinoma

A double-blind randomized clinical trial of a topical herbal extract (Z-HE) vs. systemic meglumine antimoniate for the treatment of cutaneous leishmaniasis in Iran

Erysipeloid leishmaniasis : an unusual clinical presentation

Using deep-learning to predict outcome of patients with Parkinson's disease

Machine Learning Methods for Optimal Prediction of Outcome in Parkinson's Disease

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