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Issues And Trends In Healthcare Delivery System01:29

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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Latest Developments in Artificial Intelligence and Machine Learning Models in General Pediatric Surgery.

Hesham Elsayed1, Georg Singer1, Tristan Till2

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European Journal of Pediatric Surgery : Official Journal of Austrian Association of Pediatric Surgery ... [Et Al] = Zeitschrift Fur Kinderchirurgie
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Summary
This summary is machine-generated.

Artificial intelligence (AI) and machine learning (ML) show promise in pediatric surgery for diagnosis and prediction. Broader implementation requires collaborative research, robust data, and AI training for surgeons.

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Area of Science:

  • Pediatric Surgery
  • Medical Artificial Intelligence
  • Machine Learning in Healthcare

Background:

  • Artificial intelligence (AI) and machine learning (ML) are transforming healthcare, yet their use in pediatric surgery is limited.
  • Challenges include rare conditions, small datasets, and a lack of surgeon training in AI.

Purpose of the Study:

  • To review current AI and ML applications in general pediatric surgery.
  • To focus on key conditions: appendicitis, necrotizing enterocolitis, Hirschsprung's disease, congenital diaphragmatic hernia, and biliary atresia.

Main Methods:

  • Narrative review of AI/ML applications in pediatric surgery.
  • Summarized AI use in image analysis, diagnostics, prediction, monitoring, and histopathology for five key conditions.
  • Highlighted novel tools like explainable AI, NLP, and wearables.

Main Results:

  • AI/ML demonstrate promising diagnostic and prognostic capabilities in pediatric surgical conditions.
  • Current models often need external validation and standardization.
  • Explainable AI, NLP, and wearables are emerging tools.

Conclusions:

  • AI and ML have significant potential to enhance pediatric surgical care.
  • Widespread adoption necessitates multicenter collaboration, large datasets, and specialized AI education for surgeons.