scholarly journals An Optimal Decision Procedure for MPNL over the Integers

2011 ◽  
Vol 54 ◽  
pp. 192-206
Author(s):  
Davide Bresolin ◽  
Angelo Montanari ◽  
Pietro Sala ◽  
Guido Sciavicco
Keyword(s):  
Decision Procedure ◽  
Optimal Decision

An Optimal Decision Procedure for Right Propositional Neighborhood Logic

2006 ◽  
Vol 38 (1-3) ◽  
pp. 173-199 ◽  
Author(s):  
Davide Bresolin ◽  
Angelo Montanari ◽  
Guido Sciavicco
Keyword(s):  
Decision Procedure ◽  
Optimal Decision

scholarly journals Tableau reductions: Towards an optimal decision procedure for the modal necessity

2016 ◽  
Vol 17 ◽  
pp. 14-24 ◽  
Author(s):  
Joanna Golińska-Pilarek ◽  
Emilio Muñoz-Velasco ◽  
Angel Mora
Keyword(s):  
Decision Procedure ◽  
Optimal Decision

A Decision Procedure for Bit-Vector Arithmetic

1998 ◽  
Author(s):  
Clark W. Barrett ◽  
David L. Dill ◽  
Jeremy R. Levitt
Keyword(s):  
Decision Procedure ◽  
Bit Vector

scholarly journals Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Muhammad Javed Iqbal ◽  
Zeeshan Javed ◽  
Haleema Sadia ◽  
Ijaz A. Qureshi ◽  
Asma Irshad ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cancer Diagnosis ◽  
Disease Risk ◽  
Clinical Applications ◽  
Optimal Decision ◽  
Great Promise ◽  
Time Range ◽  
Base System ◽  
The Future

AbstractArtificial 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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