Using artificial intelligence to bring evidence-based medicine a step closer to making the individual difference

2007 ◽  
Vol 32 (1) ◽  
pp. 11-18 ◽  
Author(s):  
B. Sissons ◽  
W. A. Gray ◽  
A. Bater ◽  
D. Morrey
Keyword(s):  
Artificial Intelligence ◽  
Individual Difference ◽  
Evidence Based Medicine ◽  
Evidence Based ◽  
The Individual ◽  
Based Medicine

scholarly journals Evidence-Based Medicine in judicial decisions concerning right to healthcare

2016 ◽  
Vol 14 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Eduardo Rocha Dias ◽  
Geraldo Bezerra da Silva Junior
Keyword(s):  
Health Insurance ◽  
Evidence Based Medicine ◽  
Private Health Insurance ◽  
Scientific Evidence ◽  
Federal Court ◽  
Public Healthcare ◽  
Evidence Based ◽  
Unified Health System ◽  
The Individual ◽  
Based Medicine

ABSTRACT Objective To analyze, from the examination of decisions issued by Brazilian courts, how Evidence-Based Medicine was applied and if it led to well-founded decisions, searching the best scientific knowledge. Methods The decisions made by the Federal Courts were searched, with no time limits, at the website of the Federal Court Council, using the expression “Evidence-Based Medicine”. With regard to decisions issued by the court of the State of São Paulo, the search was done at the webpage and applying the same terms and criterion as to time. Next, a qualitative analysis of the decisions was conducted for each action, to verify if the patient/plaintiff’s situation, as well as the efficacy or inefficacy of treatments or drugs addressed in existing protocols were considered before the court granted the provision claimed by the plaintiff. Results In less than one-third of the decisions there was an appropriate discussion about efficacy of the procedure sought in court, in comparison to other procedures available in clinical guidelines adopted by the Brazilian Unified Health System (Sistema Único de Saúde) or by private health insurance plans, considering the individual situation. The majority of the decisions involved private health insurance plans (n=13, 68%). Conclusion The number of decisions that did consider scientific evidence and the peculiarities of each patient was a concern. Further discussion on Evidence-Based Medicine in judgments involving public healthcare are required.

scholarly journals Pearls for Interpreting Neurosurgical Systematic Reviews and Meta-Analyses: Lessons From a Collaborative Effort

Neurosurgery ◽  
2020 ◽  
Vol 87 (3) ◽  
pp. 435-441 ◽  
Author(s):  
Victor M Lu ◽  
Christopher S Graffeo ◽  
Avital Perry ◽  
Michael J Link ◽  
Fredric B Meyer ◽  
...  
Keyword(s):  
Systematic Reviews ◽  
Evidence Based Medicine ◽  
Lessons Learned ◽  
Evidence Based ◽  
Cranial Neuralgia ◽  
The Individual ◽  
Meta Analyses ◽  
Based Medicine ◽  
Over Time

Abstract Systematic reviews and meta-analyses in the neurosurgical literature have surged in popularity over the last decade. It is our concern that, without a renewed effort to critically interpret and appraise these studies as high or low quality, we run the risk of the quality and value of evidence-based medicine in neurosurgery being misinterpreted. Correspondingly, we have outlined 4 major domains to target in interpreting neurosurgical systematic reviews and meta-analyses based on the lessons learned by a collaboration of clinicians and academics summarized as 4 pearls. The domains of (1) heterogeneity, (2) modeling, (3) certainty, and (4) bias in neurosurgical systematic reviews and meta-analyses were identified as aspects in which the authors’ approaches have changed over time to improve robustness and transparency. Examples of how and why these pearls were adapted were provided in areas of cranial neuralgia, spine, pediatric, and neuro-oncology to demonstrate how neurosurgical readers and writers may improve their interpretation of these domains. The incorporation of these pearls into practice will empower neurosurgical academics to effectively interpret systematic reviews and meta-analyses, enhancing the quality of our evidence-based medicine literature while maintaining a critical focus on the needs of the individual patients in neurosurgery.

scholarly journals Technology of Supporting Medical Decision-Making Using Evidence-Based Medicine and Artificial Intelligence

2020 ◽  
Vol 176 ◽  
pp. 1703-1712
Author(s):  
Georgy Lebedev ◽  
Eduard Fartushnyi ◽  
Igor Fartushnyi ◽  
Igor Shaderkin ◽  
Herman Klimenko ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Evidence Based Medicine ◽  
Medical Decision Making ◽  
Medical Decision ◽  
Evidence Based ◽  
Based Medicine

Why, in medicine, evidence is still more important than narratives or values? Or “The importance of being evident.”

2017 ◽  
Vol 5 (3) ◽  
pp. 357
Author(s):  
Marie-Caroline Schulte
Keyword(s):  
Medical Treatment ◽  
Evidence Based Medicine ◽  
Population Based ◽  
Evidence Based ◽  
Research And Practice ◽  
Actual Patient ◽  
The Individual ◽  
Based Medicine ◽  
Do So ◽  
Evidence Hierarchies

The importance of being evident is what counts for medicine. The diagnosis must be evident and the treatment must be based on evidence. If that evidence is and always must be based on statistics, as we have seen, it becomes questionable. Evidence is good when it is robust and when it fits the individual patient. Only then does evidence-based medicine (EBM), make sense and only then the patient can be sure to be treated in the best possible way. EBM, the movement of medicine that is strictly based on evidence which is judged in a hierarchical order, is under scrutiny and heavily criticised, chiefly because it has lost the patient out of its focus. Numbers are more important than the individual diagnosis and treatment is administered according to population-based statistics and not ‘made to order’. Although this criticism is very valid, the solution cannot be to simply replace EBM with something else, but the solution must be to still base medicine and medical treatment on the best available evidence we have, while putting the patient back into focus. In order to do so, it is important to topple evidence hierarchies, to divide EBM into research and practice and to acknowledge that sometimes the statistical best evidence is not the best evidential treatment for the actual patient.

Quality Assurance in Evidence-Based Medicine

2010 ◽  
pp. 86-99
Author(s):  
Ioannis Apostolakis ◽  
Periklis Valsamos ◽  
Iraklis Varlamis
Keyword(s):  
Quality Assurance ◽  
Evidence Based Medicine ◽  
Medical Information ◽  
Building Blocks ◽  
Careful Examination ◽  
Evidence Based ◽  
The Individual ◽  
Based Medicine ◽  
Critical Overview

Evidence-based medicine (EBM) refers to the careful examination of all the available evidence when making decisions about the care of the individual patient. It assumes that well known medical practices and solutions are combined with the patient’s preferences and necessities in order to provide the most appropriate solution per case. The abundance of medical information in the web, the expansion of Semantic Web and the evolution of search services allowed the easier retrieval of scientific articles. Although the available infrastructure exists and continuously improves in performance, EBM still remains a complicated and sensitive process of high importance and has a need for Quality Assurance (QA). The purpose of this chapter is twofold: first, to provide an introduction on the concepts of Evidence-based Medicine, and second, to stress the necessity for structured methodologies that will assure the quality of the EBM process and ameliorate the final recommendations therapy. Since evidences are the building blocks of EBM, we capitalize on their quality and provide a critical overview of the existing methodologies in Quality Assurance of evidences.

Paradoxes of evidence-based medicine in lower-grade glioma

Neurology ◽  
2018 ◽  
Vol 91 (14) ◽  
pp. 657-662 ◽  
Author(s):  
Hugues Duffau
Keyword(s):  
Evidence Based Medicine ◽  
Evidence Based ◽  
Lower Grade ◽  
Brain Organization ◽  
Large Variability ◽  
Individual Level ◽  
Standardized Protocol ◽  
Lower Grade Glioma ◽  
The Individual ◽  
Based Medicine

Brain lower-grade gliomas (LGG) usually occur in young adults who enjoy an active life. This tumor has a high risk of malignant transformation resulting in neurologic deterioration and finally death. Early and multistage therapeutic management can increase survival over 10 years. Preservation of functional neural networks and quality of life is crucial. In the era of evidence-based medicine, the issues discussed are those associated with the design, analysis, and clinical application of randomized controlled trials (RCTs) for LGG. RCTs should take account of the following: considerable variability in the natural course of LGG; limited prognostic value of molecular biology at the individual level; large variability of brain organization across patients; technical and conceptual progress of therapies over years; combination or repetition of iterative treatments, taken as a whole and not only in isolation; and long-term consequences on oncologic and functional outcomes. As it is difficult to translate the results of an RCT into benefits for a unique patient with LGG, personalized decisions must be made by considering the tumor behavior, individual pattern of neuroplasticity, and patient needs, and not by administrating a standardized protocol exclusively based on an RCT.

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