Improving Healthcare Facilities with AI
Artificial Intelligence (AI) is increasingly being used in healthcare as it can advance research and provide increasingly specialized treatment to patients. This includes the following:
• Bringing in the Change
IBM Watson cognitive computing has been deployed over the years in research centers and hospitals, but beneficial results have been observed recently. By partnering with New York-based Memorial Sloan Kettering Cancer Centre (MSK), Watson Oncology is being trained to interpret the clinical information of cancer patients to identify evidence-based individualized treatment options. MSK aims to create a resource aiding in taking more informed decisions for cancer patients. This collaboration is expected to decrease the time taken for the latest research and evidence to influence clinical trials, improve the synthesis of available information and increase patient care across the oncology community.
• Publishing Scientific Papers Efficiently
Language processing, using AI technology, can be applied to help create journals for articles to be published in scientific journals. sciNote, which created an open space electronic lab notebook (ELN) by the same name, uses AI in its ELN software. Using this manuscript writer add-on, researchers can generate drafts of scientific manuscripts by utilizing the data and references stored on the platform. sciNote is the first ELN to use AI to put data together to ultimately reduce the time taken to write a research paper.
• Diagnosing Diseases using AI
The Poland-based Future Processing is an example of research enabled through AI. It simplifies the use of tools to make the process of diagnosis simple, affordable and accurate. The segment of medical imaging solutions works with medical image experts, clinics and research institutions across the globe to develop software that can process and analyze images. The major area of focus is currently dynamic contrast-enhanced imaging and analyzing computed tomography (CT) images, which is expected to lead to the increased use of CT scans exclusively to diagnose and detect cancer.
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