Artificial Intelligence in Digital Pathology: Understanding the Molecular Basis of Diseases
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If you’ve ever dreamed of a life with a faster, more effective treatment for the common cold, it might be closer than you think. Artificial intelligence (AI) is helping to improve digital pathology and assist experts in identifying the basis of disease. AI is also changing the way commercial pathology labs read specimen images and make diagnoses. Digital image data lets pathologists quickly send information to specialists, while machine learning coupled with digital imaging software is helping to reduce the chance of human error.
With these detailed insights into the origins and makeup of different diseases, researchers can more effectively understand how they operate and how to treat them.
Microscopy Advances Make AI More Effective
Pathologists are putting their traditional optical microscopes aside and are using AI algorithms to identify unusual areas and structures. AI’s more comprehensive diagnoses let lab personnel and physicians identify and target therapies for individual patients and provide better care to patients.
Digital pathology now allows pathologists to read multiple slides simultaneously. AI algorithms can visually annotate and highlight slides with information to help aid with diagnoses. Digitization even allows colleagues to collaborate and make the process even faster or consult for a second opinion. As digital pathology equipment advances, artificial intelligence algorithms will have better images to predict patient outcome.
Artificial Intelligence and Pathologists Work Together
Researchers are leveraging AI to optimize workflow and make digital pathology more efficient for pathologists. As is the case with many other fields making use of AI, pathology has repetitive tasks that can be automated with AI. Pathologists can focus instead on producing accurate diagnoses.
One key advantage is AI doesn’t require any actual knowledge of the disease. It can simply learn patterns of images. Once trained, it can help to predict the outcome of patients directly from the images. Training AI in digital pathology is a challenge because it requires a good ground truth, but diagnoses are often subjective and show disagreement among pathologists.
Pathologists are expected to gather all the information available, provide a diagnosis, and help guide the patient throughout their care. AI algorithms could never replace that kind of personal attention; however, AI will allow pathologists more time to devote to complex cases since it will take over the task of processing large amounts of the data.
The Benefits of Using AI in Digital Pathology
AI in digital pathology is only in its beginning stages. To make the most effective use of AI, pathologists will use their understanding of how the AI was trained and tested. Labs will have to ultimately decide if AI can help improve their clinical and operational performance; however, it will likely be effective when it comes to sorting images, helping to prioritize cases, and identifying high-risk regions of interest.
Artificial intelligence algorithms are already using microscopy and other imaging techniques to find bone fractures, eye disease, and signs of a stroke. AI is also being used in biochemistry, immunology, and genetics. AI has the potential to find patterns that researchers may overlook. It is also helping to develop biomarker detection tools to help pathologists choose the best drug or therapy for a particular patient. It’s very exciting to know all these potential benefits could be on the horizon.
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