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Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future
by
Raza, Shahid
, Sadia, Haleema
, Malik, Kausar
, Abbas, Asif
, Irshad, Asma
, Pezzani, Raffaele
, Qureshi, Ijaz A.
, Javed, Zeeshan
, Iqbal, Muhammad Javed
, Ahmed, Rais
, Sharifi-Rad, Javad
in
Algorithms
/ Artificial intelligence
/ Autonomous vehicles
/ Big Data
/ Biology
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain
/ Cancer
/ Cancer diagnosis
/ Cancer Research
/ Cell Biology
/ Cognitive ability
/ Datasets
/ Decision making
/ Design
/ Diagnosis
/ Disease
/ Empowerment
/ Epigenetics
/ Gene expression
/ Gene mapping
/ Genetic diversity
/ Information management
/ Learning algorithms
/ Machine learning
/ Medical diagnosis
/ Medical research
/ Medical technology
/ Medicine
/ Neural networks
/ Pharmaceutical industry
/ Protein interaction
/ Proteins
/ Review
/ Robotics
/ Semantic web
/ Semantics
/ Surgery
/ Therapeutic applications
/ Therapeutic interventions
/ Treatment
2021
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Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future
by
Raza, Shahid
, Sadia, Haleema
, Malik, Kausar
, Abbas, Asif
, Irshad, Asma
, Pezzani, Raffaele
, Qureshi, Ijaz A.
, Javed, Zeeshan
, Iqbal, Muhammad Javed
, Ahmed, Rais
, Sharifi-Rad, Javad
in
Algorithms
/ Artificial intelligence
/ Autonomous vehicles
/ Big Data
/ Biology
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain
/ Cancer
/ Cancer diagnosis
/ Cancer Research
/ Cell Biology
/ Cognitive ability
/ Datasets
/ Decision making
/ Design
/ Diagnosis
/ Disease
/ Empowerment
/ Epigenetics
/ Gene expression
/ Gene mapping
/ Genetic diversity
/ Information management
/ Learning algorithms
/ Machine learning
/ Medical diagnosis
/ Medical research
/ Medical technology
/ Medicine
/ Neural networks
/ Pharmaceutical industry
/ Protein interaction
/ Proteins
/ Review
/ Robotics
/ Semantic web
/ Semantics
/ Surgery
/ Therapeutic applications
/ Therapeutic interventions
/ Treatment
2021
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Do you wish to request the book?
Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future
by
Raza, Shahid
, Sadia, Haleema
, Malik, Kausar
, Abbas, Asif
, Irshad, Asma
, Pezzani, Raffaele
, Qureshi, Ijaz A.
, Javed, Zeeshan
, Iqbal, Muhammad Javed
, Ahmed, Rais
, Sharifi-Rad, Javad
in
Algorithms
/ Artificial intelligence
/ Autonomous vehicles
/ Big Data
/ Biology
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain
/ Cancer
/ Cancer diagnosis
/ Cancer Research
/ Cell Biology
/ Cognitive ability
/ Datasets
/ Decision making
/ Design
/ Diagnosis
/ Disease
/ Empowerment
/ Epigenetics
/ Gene expression
/ Gene mapping
/ Genetic diversity
/ Information management
/ Learning algorithms
/ Machine learning
/ Medical diagnosis
/ Medical research
/ Medical technology
/ Medicine
/ Neural networks
/ Pharmaceutical industry
/ Protein interaction
/ Proteins
/ Review
/ Robotics
/ Semantic web
/ Semantics
/ Surgery
/ Therapeutic applications
/ Therapeutic interventions
/ Treatment
2021
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Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future
Journal Article
Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future
2021
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Overview
Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. The exponential growth of AI in the last decade is evidenced to be the potential platform for optimal decision-making by super-intelligence, where the human mind is limited to process huge data in a narrow time range. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused to bring AI technology to the clinics safely and ethically. AI-based assistance to pathologists and physicians could be the great leap forward towards prediction for disease risk, diagnosis, prognosis, and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis and treatment are the future of medical guidance towards faster mapping of a new treatment for every individual. By using AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. In this review, we focused to present game-changing technology of the future in clinics, by connecting biology with Artificial Intelligence and explain how AI-based assistance help oncologist for precise treatment.
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