Clinical Decision Support Systems: A Visual Survey

Farooq, Kamran; Khan, Bisma S.; Niazi, Muaz A.; Leslie, Stephen J; Hussain, Amir

doi:10.31449/inf.v42i4.1571

Cited by 6 publications

(3 citation statements)

References 42 publications

(53 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several studies have pointed to the role of various CDSSs in reducing drug errors. 10,24,[35][36][37][38] Especially, CPOE coupled with CDSS has been able to significantly reduce therapeutic medication errors based on the rules derived from the therapeutic protocols. 26,[38][39][40][41] The results of this study on alert cases deviating from the chemotherapy protocol by CPDSS showed that this system could help find chemotherapy drug errors.…”

Section: Discussionmentioning

confidence: 99%

A Clinical Decision Support System for Increasing Compliance with Protocols in Chemotherapy of Children with Acute Lymphoblastic Leukemia

et al. 2022

View full text Add to dashboard Cite

Objective: In this survey, a protocol-based Chemotherapy Prescription Decision Support System (CPDSS) was designed and evaluated to reduce medication errors in the chemotherapy process of children with ALL. Methods: The CPDSS algorithm was extracted by the software development team based on the protocol used by doctors to treat children with ALL. The ASP.Net MVC and SQL Server 2016 programming languages were used to develop the system. A 3-step evaluation (technical, retrospective, and user satisfaction) was performed on CPDSS designed at 2 children’s hospitals in Tehran. The data were analyzed using descriptive statistics. At the technical evaluation step, users provided recommendations included in the system. Results: In the retrospective CPDSS evaluation step, 1281 prescribed doses of the drugs related to 30 patients were entered into the system. CPDSS detected 735 cases of protocol deviations and 57 (95%, CI = 1.25-2.55) errors in prescribed chemotherapy for children with ALL. In the user satisfaction evaluation, the users approved two dimensions of the user interface and functionality of the system. Conclusions: With the provision of alerts, the CPDSS can help increase compliance with chemotherapy protocols and decrease the chemotherapy prescribing errors that can improve patient safety.

show abstract

Section: Discussionmentioning

confidence: 99%

A Clinical Decision Support System for Increasing Compliance with Protocols in Chemotherapy of Children with Acute Lymphoblastic Leukemia

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Quality of life is significantly impacting on receiving regular medication, and patients should thus get it. While patients with eating disorders are identified, they also get dietary guidance to help them develop appropriate treatment plans [107]. As a further point, there are so many challenges that occur during the diagnosis of GC.…”

Section: Incorporated Into the Healthcare Sectormentioning

confidence: 99%

Diagnosis of Gastric Cancer Using Machine Learning Techniques in Healthcare Sector: A Survey

Jamil

2022

IJCAI

View full text Add to dashboard Cite

Many researchers are trying hard to minimize the incidence of cancers, mainly GC. For GC, the five-year survival rate is generally 5-25%, but for EGC, it is almost up to 90%. Among the cancers, GC is very deadly. It is difficult for doctors to assess its threat to patients as it requires years of medical practice and rigorous testing. The healthcare sector has benefitted from AI for the early diagnosis or classification of GC. However, the current AI-based techniques need further improvement in clinical testing. Heterogeneous GC characterization requires more optimized methods for early detection of GC because of its type and severity. Hence, it is essential to investigate this area further and develop more optimized approaches for early diagnosis. Early detection will increase the chances of successful treatments. In this study, we have conducted a literature survey detailing the role of AI in the healthcare sector for GC diagnosis. We discuss basic principles, advantages and disadvantages, training and testing of data, and integration of applications like DSS, CDSS, KDD, ML, DM, BD, and DL, and their relevance to the healthcare industry. The study focuses on the application of ML techniques used in the diagnosis of GC. This review paper also introduces DM techniques, their application in the healthcare industry, limitations, roles, and operational challenges. These assist pathologists in helping minimize their workload while increasing diagnostic accuracy. These techniques will further assist medical practitioners with their decision-making process. Povzetek: Raziskava o uporabi tehnik strojnega učenja pri diagnostiki raka želodca v zdravstvenem sektorju.

show abstract

“…Research method for bibliographic analysis of Marketing research adopted from(Farooq, Khan, Niazi, Leslie, & Hussain, 2018) …”

mentioning

confidence: 99%

The State of the Art in Smart Grid Domain: A Network Modeling Approach

Akram

Noor

Manzoor

2020

BRAIN

View full text Add to dashboard Cite

. Scientometric analysis is a useful tool to perform a comprehensive bibliographic review. It allows not only to understand the key areas of research but also provide visual representation of each entity involve in the research. In this study, we provide a detailed statistical as well as visual analysis of agent-based smart grid research by adopting complex network-based analytical approach. The study covers all scientific literature available online in Web of Science database. We are interested in identification of key papers, authors, and journals. Furthermore, we also investigate core countries, institutions, and categories.

show abstract

Clinical Decision Support Systems: A Visual Survey

Cited by 6 publications

References 42 publications

A Clinical Decision Support System for Increasing Compliance with Protocols in Chemotherapy of Children with Acute Lymphoblastic Leukemia

A Clinical Decision Support System for Increasing Compliance with Protocols in Chemotherapy of Children with Acute Lymphoblastic Leukemia

Diagnosis of Gastric Cancer Using Machine Learning Techniques in Healthcare Sector: A Survey

The State of the Art in Smart Grid Domain: A Network Modeling Approach

Contact Info

Product

Resources

About