Tuesday, January 18, 2022
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Smart Healthcare Solutions – AI Healthcare

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The Artificial intelligence (AI) technologies have played a pivotal role in revolutionising the technology and by and large, has become present in modern business and everyday life is also steadily being applied to healthcare. The use of artificial intelligence in healthcare has the potential to assist healthcare providers in many aspects of patient care and administrative processes. Most AI and healthcare technologies have strong relevance to the healthcare field, but the tactics they support can vary significantly.

The use of artificial intelligence in healthcare can perform just as well or better than humans at certain procedures, such as diagnosing disease, it will be a significant number of years before AI in healthcare replaces humans for a broad range of medical tasks.

The use of AI and the Internet of Medical Things (IoMT) in consumer health applications is already helping people. Technology applications and apps encourage healthier behavior in individuals and help with the proactive management of a healthy lifestyle. Additionally, AI increases the ability for healthcare professionals to better understand the day-to-day patterns and needs of the people they care for, and with that understanding, they are able to provide better feedback, guidance, and support for staying healthy

AI is already being used to detect diseases, such as cancer, more accurately and in their early stages. The use of AI is enabling the review and translation of mammograms 30 times faster with 99% accuracy, reducing the need for unnecessary biopsies.

The proliferation of consumer wearables and other medical devices combined with AI is also being applied to oversee early-stage heart disease, enabling doctors and other caregivers to better monitor and detect potentially life-threatening episodes at earlier, more treatable stages.

Computer vision has mainly been based on statistical signal processing but is now shifting more toward the application of artificial neural networks as the choice for learning methods. Here, DL is used to engineer computer vision algorithms for classifying images of lesions in the skin and other tissues. Video data is estimated to contain 25 times the amount of data from high-resolution diagnostic images such as CT and could thus provide a higher data value based on resolution over time. Video analysis is still premature but has great potential for clinical decision support. As an example, video analysis of a laparoscopic procedure in real-time has resulted in 92.8% accuracy in the identification of all the steps of the procedure and surprisingly, the detection of missing or unexpected steps

Extract 2D images from DICOM files and apply the appropriate tools to perform exploratory data analysis on them. Build different AI models for different clinical scenarios that involve 2D images and learn how to position AI tools for regulatory approval. Design and apply machine learning algorithms to solve the challenging problems in 3D medical imaging and how to integrate the algorithms into the clinical workflow.

AI and collaborative robots have revolutionized surgeries in terms of their speed, and depth while making delicate incisions. Since robots don’t get tired, the issue of fatigue in the middle of lengthy and crucial procedures is eliminated.AI machines are capable of employing data from past operations to develop new surgical methods. The preciseness of these machines reduces the possibility of tremors or any unintended or accidental movements during the surgeries.

AI systems facilitate virtual nursing assistants that can perform a range of tasks from conversing with patients to directing them to the best and effective care unit. These virtual nurses are available 24/7 and can respond to queries as well as examine patients and provide instant solutions.

Presently many AI-powered applications of virtual nursing assistants presently enable more regular interactions between patients and care providers between office visits to avoid any unnecessary hospital visits.

Thus we see how AI has totally revolutionised the healthcare segment and will continue to do so.

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