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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
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

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Artificial intelligence-based computer vision in surgery: Recent advances and future perspectives.

Daichi Kitaguchi¹, Nobuyoshi Takeshita¹, Hiro Hasegawa¹

¹Surgical Device Innovation Office National Cancer Center Hospital East Kashiwa Japan.

Annals of Gastroenterological Surgery

|February 2, 2022

Summary

This summary is machine-generated.

Advancements in computer vision (CV) and artificial intelligence (AI) are revolutionizing minimally invasive surgery (MIS). Automating surgical video analysis promises enhanced decision-making and future surgical automation.

Keywords:

artificial intelligence computer vision decision‐making machine learning minimally invasive surgery

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Area of Science:

Computer Science
Medical Technology
Surgical Innovation

Background:

Minimally invasive surgery (MIS) increasingly utilizes advanced technologies, generating vast amounts of data from surgical videos.
Automating the analysis of this complex surgical video data is crucial for maximizing its utility and enabling research.
Computer vision (CV) offers methods to automate tasks typically performed by the human visual system, including image and video recognition.

Purpose of the Study:

To summarize recent advancements in artificial intelligence (AI)-related research and development for surgical applications.
To explore the future perspectives of applying AI and CV in minimally invasive surgery (MIS).
To highlight the potential of automated surgical video analysis for future surgical innovations.

Main Methods:

Review of recent literature on AI and CV applications in surgery.
Analysis of technological advancements in surgical video data extraction and interpretation.
Exploration of AI-based image recognition techniques applied to complex surgical video data.

Main Results:

AI-based image recognition has shown significant progress, nearing human-level performance in simpler tasks.
Surgical video recognition presents complex challenges but holds immense potential for MIS.
Effective application of CV in MIS can lead to intraoperative decision-making support and image-guided surgery.

Conclusions:

AI and CV are pivotal for unlocking the full potential of data generated in modern surgery.
Automated analysis of surgical videos is essential for driving innovation and potentially realizing automated surgery.
Continued research and development in AI for surgery will pave the way for significant future advancements.