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Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Machine Learning and Artificial Intelligence for Surgical Decision Making.

Saskya Byerly¹, Lydia R Maurer², Alejandro Mantero³

¹Department of Surgery, University of Tennessee Health Science Center, Memphis, Tennessee, USA.

Surgical Infections

|July 16, 2021

Summary

This summary is machine-generated.

Machine learning (ML) and artificial intelligence (AI) are increasingly vital in medical research, offering advanced data interpretation for surgical infection studies. This review equips surgeons with essential ML/AI knowledge for critical evaluation.

Keywords:

artificial intelligence big data machine learning

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Area of Science:

Medical research
Surgical infections
Data science

Background:

Machine learning (ML) and artificial intelligence (AI) are increasingly utilized in medical research.
Expanding clinical data availability fuels the growth of ML/AI applications.
These techniques offer advanced data interpretation beyond traditional statistical methods.

Purpose of the Study:

To provide practicing surgeons and clinicians with an overview of ML/AI in surgical infection research.
To outline the current and future roles of ML/AI in this field.
To establish a baseline literacy for critically assessing ML/AI projects.

Main Methods:

Literature review of ML/AI applications in surgical infections.
Conceptual overview of ML/AI techniques.
Illustration of concrete examples and case studies.

Main Results:

ML/AI techniques enable complex data interpretation and identification of non-linear relationships.
Examples include ML/AI in clinical decision support and therapy discovery using deep reinforcement learning.
The review highlights the growing importance and application of these methods.

Conclusions:

Artificial intelligence and ML are essential tools in surgical infection research.
Understanding ML/AI is crucial for surgeons to critically evaluate research and applications.
This review aims to enhance clinician literacy in ML/AI for improved research assessment.