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Artificial intelligence in cancer diagnosis: Opportunities and challenges.
S Alshuhri, Mohammed; Al-Musawi, Sada Ghalib; Al-Alwany, Ameen Abdulhasan; Uinarni, Herlina; Rasulova, Irodakhon; Rodrigues, Paul; Alkhafaji, Adnan Taan; Alshanberi, Asim Muhammed; Alawadi, Ahmed Hussien; Abbas, Ali Hashim.
Afiliação
  • S Alshuhri M; Radiology and Medical Imaging Department, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University, Kharj, Saudi Arabia.
  • Al-Musawi SG; College of Pharmacy, National University of Science and Technology, Dhi Qar, Iraq.
  • Al-Alwany AA; University of Baghdad/ College of Medicine, Baghdad, Iraq.
  • Uinarni H; Department of Anatomy, School of Medicine and Health Sciences Atma Jaya Catholic University of Indonesia, Indonesia; Radiology department of Pantai Indah Kapuk Hospital Jakarta, Jakarta, Indonesia. Electronic address: Dr.uinarniherlina@outlook.com.
  • Rasulova I; School of Humanities, Natural & Social Sciences, New Uzbekistan University, 54 Mustaqillik Ave., Tashkent 100007, Uzbekistan; Department of Public Health, Samarkand State Medical University, Amir Temur Street 18, Samarkand, Uzbekistan.
  • Rodrigues P; Department of Computer Engineering, College of Computer Science, King Khalid University, Al-Faraa, Abha, Asir, Kingdom of Saudi Arabia.
  • Alkhafaji AT; Cardiology Department, College of Medicine, Al-Ayen University, Dhi-Qar, Iraq.
  • Alshanberi AM; Department of Community Medicine & Pilgrim Healthcare, Umm Alqura University, Makkah 24382, Saudi Arabia; General Medicine Practice Program, Batterjee Medical College, Jeddah 21442, Saudi Arabia.
  • Alawadi AH; College of Technical Engineering, the Islamic University, Najaf, Iraq; College of Technical Engineering, the Islamic University of Al Diwaniyah, Iraq; College of Technical Engineering, the Islamic University of Babylon, Iraq.
  • Abbas AH; College of Technical Engineering, Imam Ja'afar Al-Sadiq University, Al-Muthanna 66002, Iraq.
Pathol Res Pract ; 253: 154996, 2024 Jan.
Article em En | MEDLINE | ID: mdl-38118214
ABSTRACT
Since cancer is one of the world's top causes of death, early diagnosis is critical to improving patient outcomes. Artificial intelligence (AI) has become a viable technique for cancer diagnosis by using machine learning algorithms to examine large volumes of data for accurate and efficient diagnosis. AI has the potential to alter the way cancer is detected fundamentally. Still, it has several disadvantages, such as requiring a large amount of data, technological limitations, and ethical concerns. This overview looks at the possibilities and restrictions of AI in cancer detection, as well as current applications and possible future developments. We can better understand how to use AI to improve patient outcomes and reduce cancer mortality rates by looking at its potential for cancer detection.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Inteligência Artificial / Neoplasias Limite: Humans Idioma: En Revista: Pathol Res Pract / Pathol. res. pract / Pathology research and practice (Print) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Arábia Saudita

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Inteligência Artificial / Neoplasias Limite: Humans Idioma: En Revista: Pathol Res Pract / Pathol. res. pract / Pathology research and practice (Print) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Arábia Saudita