Artificial Intelligence in Drug Treatment

2020 ◽  
Vol 60 (1) ◽  
pp. 353-369 ◽  
Author(s):  
Eden L. Romm ◽  
Igor F. Tsigelny
Keyword(s):  
Artificial Intelligence ◽  
Drug Treatment ◽  
Drug Interactions ◽  
Drug Target ◽  
Process Selection ◽  
Treatment Protocols ◽  
Optimal Drug ◽  
Chemical Descriptors ◽  
Pharmacodynamic Data ◽  
Selection Of

The most common applications of artificial intelligence (AI) in drug treatment have to do with matching patients to their optimal drug or combination of drugs, predicting drug-target or drug-drug interactions, and optimizing treatment protocols. This review outlines some of the recently developed AI methods aiding the drug treatment and administration process. Selection of the best drug(s) for a patient typically requires the integration of patient data, such as genetics or proteomics, with drug data, like compound chemical descriptors, to score the therapeutic efficacy of drugs. The prediction of drug interactions often relies on similarity metrics, assuming that drugs with similar structures or targets will have comparable behavior or may interfere with each other. Optimizing the dosage schedule for administration of drugs is performed using mathematical models to interpret pharmacokinetic and pharmacodynamic data. The recently developed and powerful models for each of these tasks are addressed, explained, and analyzed here.

scholarly journals AI – New Avenue for Drug Discovery and Optimization

2021 ◽  
pp. 1-9
Author(s):  
Rupesh Dudhe ◽  
Anshu Chaudhary Dudhe ◽  
Rupesh Dudhe ◽  
Suhas N. Sakarkar ◽  
Omji Porwal
Keyword(s):  
Artificial Intelligence ◽  
Drug Discovery ◽  
Drug Treatment ◽  
Drug Target ◽  
Similarity Metrics ◽  
Process Selection ◽  
Treatment Protocols ◽  
Optimal Drug ◽  
Chemical Descriptors ◽  
Selection Of

The artificial intelligence (AI) used in drug treatment have to do with matching patients to their predicting drug-target or drug-drug interactions, optimal drug or combination of drugs, and optimizing treatment protocols. This review outlines some of the recently developed AI methods aiding the drug treatment and administration process. Selection of the suitable drug for a patient typically requires the patient data, such as genetics or proteomics, with drug data, like compound chemical descriptors, to score the therapeutic efficacy of drugs. The forecast of drug relations often relies on similarity metrics, pretentious that drugs with similar structures or targeted and similar behaviour or may interfere with each other. Deciding the dosage schedule for administration of drugs is performed using mathematical models to interpret pharmacokinetic and pharmacodynamics data.

Simulation of public art communication in colleges based on smart cloud platform and artificial intelligence algorithm

2020 ◽  
pp. 1-11
Author(s):  
Zhang Yingying
Keyword(s):  
Artificial Intelligence ◽  
Public Art ◽  
Optimal Path ◽  
Colleges And Universities ◽  
Cloud Platform ◽  
Current Transmission ◽  
Artificial Intelligence Algorithm ◽  
Offset Coefficient ◽  
Network Status ◽  
Selection Of

Public art communication in colleges and universities needs to be launched with the support of artificial intelligence systems. According to the current situation of public art communication in colleges and universities, this paper builds a smart cloud platform for public art communication in colleges and universities with the support of artificial intelligence algorithms. Moreover, this paper introduces the bandwidth offset coefficient to judge the change of network throughput, introduces the slice download rate difference to first judge the consistency change trend of bandwidth, and then further proposes the calculation method of bandwidth prediction value by situation. In addition, this paper proposes a flexible transmission mechanism based on smart collaborative networks. Through in-depth perception of network status and component behavior, this mechanism implements the selection of the optimal path in the network according to the current network status and user service requirements to complete the transmission of service resources. If the current transmission path fails, the mechanism should ensure the continuity and reliability of the service. The research results show that the system constructed in this paper has good performance and can be applied to practice.

Selection of the most important features affecting pistachio endocarp lesion problem using artificial intelligence techniques

2019 ◽  
Vol 246 ◽  
pp. 797-804 ◽  
Author(s):  
Somayeh Sadr ◽  
Vahid Mozafari ◽  
Hossein Shirani ◽  
Hossein Alaei ◽  
Ahmad Tajabadi Pour
Keyword(s):  
Artificial Intelligence ◽  
Artificial Intelligence Techniques ◽  
Selection Of

Optimal Drug Treatment for Cutaneous T Cell Lymphoma

BioDrugs ◽  
1997 ◽  
Vol 7 (4) ◽  
pp. 254-261
Author(s):  
Brigitte Dréno ◽  
Olivier Jumbou
Keyword(s):  
T Cell ◽  
Drug Treatment ◽  
Cell Lymphoma ◽  
T Cell Lymphoma ◽  
Cutaneous T Cell Lymphoma ◽  
Optimal Drug

Rule-Based Process Selection of Hole Making Operations for Integrated Process Planning

2005 ◽  
Author(s):  
Dusan N. Sormaz ◽  
Pravin Khurana ◽  
Ajit Wadatkar
Keyword(s):  
User Interface ◽  
Manufacturing System ◽  
Selection Procedure ◽  
Machining Process ◽  
Integrated Process ◽  
Process Selection ◽  
Rule Based ◽  
Hole Making ◽  
Significant Attention ◽  
Selection Of

Process selection as a part of CAPP has captured significant attention in CAPP research. Procedures have been developed for backward and forward algorithms in process selection. Most of these procedures lack the complete integration of process selection into CAPP system. In this paper, we present the results of the development and prototype implementation for process selection module for hole making operations for integration with Math Based Manufacturing System already in use in industrial partner. We have developed architecture and implemented module for rule-based machining process selection of hole making operations. The architecture enables the interface from the Process Selection prototype to Math Based Manufacturing System (APPS). The prototype also includes the user interface for interaction with the process selection procedure. Actions for starting prototype from APPS, performing process selection steps and sending the result back to APPS have been developed and implemented.

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