57   Artículos

 
en línea
Nirmal Acharya, Padmaja Kar, Mustafa Ally and Jeffrey Soar    
Significant clinical overlap exists between mental health and substance use disorders, especially among women. The purpose of this research is to leverage an AutoML (Automated Machine Learning) interface to predict and distinguish co-occurring mental hea... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma    
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Xinghui Li, Yang Yu, Cheng Zheng, Yue Zhang, Chuandao Shi, Lei Zhang and Hui Qiao    
Studies on the prognostic significance of preoperative radiotherapy (PERT) and postoperative radiotherapy (PORT) in patients with advanced gastric cancer (GC) remain elusive. The aim of the study was to evaluate the survival advantage of preoperative and... ver más

 
en línea
Zeyuan Zhao, Ping Li, Yongjie Dai, Zhaoe Min and Lei Chen    
Alzheimer?s disease (AD) is an irreversible neurodegenerative disease. Providing trustworthy AD progression predictions for at-risk individuals contributes to early identification of AD patients and holds significant value in discovering effective treatm... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Faisal Alshomrani, Basim S. O. Alsaedi, Cheng Wei, Magdalena Szewczyk-Bieda, Stephen Gandy, Jennifer Wilson, Zhihong Huang and Ghulam Nabi    
Over the last few years, a number of studies have quantified the role of radiomics, dynamic contrast enhancement and standard MRI (T2WI + DWI) in detecting prostate cancer; however, the aim of this paper was to assess the advantage of combining radiomics... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Nermin Abdelhakim Othman, Manal A. Abdel-Fattah and Ahlam Talaat Ali    
Because of technological advancements and their use in the medical area, many new methods and strategies have been developed to address complex real-life challenges. Breast cancer, a particular kind of tumor that arises in breast cells, is one of the mos... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Maria Carmela Groccia, Rosita Guido, Domenico Conforti, Corrado Pelaia, Giuseppe Armentaro, Alfredo Francesco Toscani, Sofia Miceli, Elena Succurro, Marta Letizia Hribal and Angela Sciacqua    
Chronic heart failure (CHF) is a clinical syndrome characterised by symptoms and signs due to structural and/or functional abnormalities of the heart. CHF confers risk for cardiovascular deterioration events which cause recurrent hospitalisations and hig... ver más
Revista: Information    Formato: Electrónico

 
en línea
Zimei Zhang, Jianwei Xiao, Shanyu Wang, Min Wu, Wenjie Wang, Ziliang Liu and Zhian Zheng    
The accurate identification of the origin of Chinese medicinal materials is crucial for the orderly management of the market and clinical drug usage. In this study, a deep learning-based algorithm combined with machine vision was developed to automatical... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Lichao Sun, Yunyun Dong, Shuang Xu, Xiufang Feng and Xiaole Fan    
Epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma (KRAS) are the most common driver genes in non-small cell lung cancer patients. However, frequent gene mutation testing raises a potential risk of cancer metastasis. In our paper, a Mut-SeRe... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Amna Al-Sayed, Mashael M. Khayyat and Nuha Zamzami    
Different data types are frequently included in clinical data. Applying machine learning algorithms to mixed data can be difficult and impact the output accuracy and quality. This paper proposes a hybrid model of unsupervised and supervised learning tech... ver más
Revista: Applied Sciences    Formato: Electrónico

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