Related Experiment Video
Updated: Jan 30, 2026
04:48
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
3.5K
[Potential applications of deep learning-based technologies in Hungarian mammography]
Dezső Ribli1, Richárd Zsuppán2, Péter Pollner3
1Komplex Rendszerek Fizikája Tanszék, Eötvös Loránd Tudományegyetem Budapest.
Orvosi Hetilap
|January 22, 2019
Summary
Deep learning offers a solution to manage vast medical data, improving patient care and diagnostics. This technology can enhance doctor-patient interactions by automating data analysis, freeing clinicians for more meaningful engagement.
Area of Science:
- Computer Science
- Medicine
- Artificial Intelligence
Background:
- Deep learning, a product of computer science, presents new opportunities and challenges for medicine.
- The increasing volume of medical data has not yet enabled personalized patient treatment.
- Current healthcare systems face challenges with suboptimal protocols due to data overload and lack of targeted information.
Purpose of the Study:
- To explore the potential of deep learning in medicine.
- To address the challenges posed by large volumes of medical data.
- To enhance the application of artificial intelligence in clinical practice.
Main Methods:
- Review of deep learning technology and its implications for healthcare.
- Analysis of current data processing limitations in medicine.
- Exploration of how AI can support clinical decision-making and patient interaction.
Main Results:
- Deep learning can help process and integrate vast amounts of medical data.
- The technology is expected to aid in overcoming current data processing limitations.
- Deep learning can potentially improve diagnostic accuracy and therapeutic strategies.
Conclusions:
- Deep learning offers significant potential for medical diagnostics and therapies, including immune therapy.
- Adopting deep learning requires overcoming fears and prejudices among healthcare professionals.
- This technology can enhance human cooperation in patient-doctor visits by automating data-intensive tasks.
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