Catalyzing IVF outcome prediction: exploring advanced machine learning paradigms for enhanced success rate prognostication.

Autor: Sadegh-Zadeh SA; Department of Computing, School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, United Kingdom., Khanjani S; Department of Computer Engineering, Razi University, Kermanshah, Iran., Javanmardi S; Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands., Bayat B; Department of Computer Engineering, Artificial Intelligence, Islamic Azad University, Malard, Iran., Naderi Z; Obstetrics and Gynaecology Department, Iran University of Medical Sciences, Tehran, Iran., Hajiyavand AM; Department of Mechanical Engineering, School of Engineering, University of Birmingham, Birmingham, United Kingdom.

Publikováno v: Frontiers in artificial intelligence [Front Artif Intell] 2024 Nov 05; Vol. 7, pp. 1392611. Date of Electronic Publication: 2024 Nov 05 (Print Publication: 2024).

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.

Autor: Nazari MJ; Computer Science and Mathematics Department, Amirkabir University of Technology, Tehran, Iran., Shalbafan M; Department of Psychiatry, Psychosocial Health Research Institute (PHRI), Mental Health Research Center, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.; Institute for Cognitive Sciences Studies, Brain and Cognition Clinic, Tehran, Iran., Eissazade N; Student Research Committee, School of Medicine, Iran University of Medical Sciences, Tehran, Iran., Khalilian E; Department of Psychiatry, Tehran University of Medical Sciences, Tehran, Iran., Vahabi Z; Neuropsychiatry Department, Tehran University of Medical Sciences, Tehran, Iran., Masjedi N; Department of Psychiatry, Tehran University of Medical Sciences, Tehran, Iran., Ghidary SS; Computer Science and Mathematics Department, Amirkabir University of Technology, Tehran, Iran., Saadat M; Department of Mechanical Engineering, School of Engineering, University of Birmingham, Birmingham, United Kingdom., Sadegh-Zadeh SA; Department of Computing, Staffordshire University, Stoke-on-Trent, United Kingdom.

Publikováno v: PloS one [PLoS One] 2024 Jun 21; Vol. 19 (6), pp. e0303699. Date of Electronic Publication: 2024 Jun 21 (Print Publication: 2024).

Artificial intelligence approaches for tinnitus diagnosis: leveraging high-frequency audiometry data for enhanced clinical predictions.

Autor: Sadegh-Zadeh SA; Department of Computing, School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, United Kingdom., Soleimani Mamalo A; Student Research Committee, Urmia University of Medical Sciences, Urmia, Iran., Kavianpour K; Department of Computer Science and Mathematics, Amirkabir University of Technology, Tehran, Iran., Atashbar H; Department of Computer Science and Mathematics, Amirkabir University of Technology, Tehran, Iran., Heidari E; Department of Computer Science and Mathematics, Amirkabir University of Technology, Tehran, Iran., Hajizadeh R; Department of Cardiology, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran., Roshani AS; Department of Otorhinolaryngology - Head and Neck Surgery, Imam Khomeini University Hospital, Urmia, Iran., Habibzadeh S; Department of Audiology, Tabriz University of Medical Sciences, Tabriz, Iran., Saadat S; Hull York Medical School, University of York, York, United Kingdom., Behmanesh M; Student Research Committee, Urmia University of Medical Sciences, Urmia, Iran., Saadat M; Department of Mechanical Engineering, School of Engineering, University of Birmingham, Birmingham, United Kingdom., Gargari SS; Student Research Committee, Urmia University of Medical Sciences, Urmia, Iran.

Publikováno v: Frontiers in artificial intelligence [Front Artif Intell] 2024 May 07; Vol. 7, pp. 1381455. Date of Electronic Publication: 2024 May 07 (Print Publication: 2024).

Advancing prognostic precision in pulmonary embolism: A clinical and laboratory-based artificial intelligence approach for enhanced early mortality risk stratification.

Autor: Sadegh-Zadeh SA; Department of Computing, School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, England, United Kingdom., Sakha H; Department of Computing, School of Digital, Technologies and Arts, Staffordshire University, Stoke-on-Trent, England, United Kingdom., Movahedi S; Azad University, Science and Research, Tehran, Iran., Fasihi Harandi A; Azad University, Science and Research, Tehran, Iran., Ghaffari S; Cardiovascular Research Centre, Tabriz University of Medical Sciences, Tabriz, Iran., Javanshir E; Cardiovascular Research Centre, Tabriz University of Medical Sciences, Tabriz, Iran., Ali SA; Health Education England West Midlands, Birmingham, England, United Kingdom., Hooshanginezhad Z; Department of Cardiovascular Medicine, Shiraz University of Medical Sciences, Shiraz, Iran., Hajizadeh R; Department of Cardiology, Urmia University of Medical Sciences, Urmia, Iran. Electronic address: hajizadh.reza@gmail.com.

Publikováno v: Computers in biology and medicine [Comput Biol Med] 2023 Dec; Vol. 167, pp. 107696. Date of Electronic Publication: 2023 Nov 11.

Dental Caries Risk Assessment in Children 5 Years Old and under via Machine Learning.

Autor: Sadegh-Zadeh SA; Department of Computing, Staffordshire University, Stoke-on-Trent ST4 2DE, UK., Rahmani Qeranqayeh A; Department of Computing, Staffordshire University, Stoke-on-Trent ST4 2DE, UK., Benkhalifa E; Department of Computing, Staffordshire University, Stoke-on-Trent ST4 2DE, UK., Dyke D; Department of Computing, Staffordshire University, Stoke-on-Trent ST4 2DE, UK., Taylor L; Department of Computing, Staffordshire University, Stoke-on-Trent ST4 2DE, UK., Bagheri M; Department of Computing, Staffordshire University, Stoke-on-Trent ST4 2DE, UK.

Publikováno v: Dentistry journal [Dent J (Basel)] 2022 Sep 01; Vol. 10 (9). Date of Electronic Publication: 2022 Sep 01.