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MedTech Outlook | Tuesday, May 16, 2023
Generative AI offers multiple advantages to healthcare that could improve the quality of patient care. By gathering patient information and analysing it, healthcare professionals can detect patterns and anomalies that could indicate health risks
FREMONT, CA: One of the most prominent challenges in the healthcare industry has been to provide personalised healthcare to patients founded on their individual needs and preferences. It necessitates multiple data collection and analysis for numerous sources such as lab tests, medical records, imaging scans, genetic tests, wearable devices, and patients themselves. This information would require to be interpreted and communicated with clarity to patients as well as clinicians to make better, informed decisions.
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Generative AI can help overcome these challenges.
It is a branch of artificial intelligence that can generate new data from existing data, such as images, audio, video, and text. It can be used for multiple other purposes, such as improving creativity, augmenting data, generating realistic simulations, and improving data quality.
This type of AI uses (NLP) models to develop speech or texts to summarise medical data, elaborate on diagnosis and treatment options, or seek relevant questions from patients or wearable devices and offer recommendations to the clinician.
Data Collection from Patients and Wearables
Generative AI in healthcare first gathers relevant data from patients and wearables or medical devices. Wearables are electric devices that can monitor multiple health indicators such as blood pressure, heart rate, oxygen saturation, activity level, and sleep quality. These devices provide real-time and continuous data that complements traditional clinical data sources, such as lab tests, imaging scans, and electronic health records (EHRs).
Data Analysis
The data obtained from patient queries and wearables are analysed using generative AI. This obtains more information about certain aspects of the health status. The aim of this is to detect any potential health issues or risks that require further attention or intervention. Generative AI can help achieve this goal by developing insights with the foundation of the analysed data.
For example, it can generate summaries or visual reports with graphs by referring to the wearable data, or it can suggest prognosis or diagnosis based on wearable data by making use of machine learning techniques to make predictions on future outcomes.
Wearables and Query Patients
The next step is to use generative AI to ask patients relevant questions, based on the results of the analyses. The goal is to gain more data about specific aspects of a patient’s health status. Generative AI can be used to create questions for patients based on the results of the analysis. For instance, it can ask patients if they have taken medication when high blood pressure was observed or their physical condition upon viewing the low heart rate on the wearable device.
The technology offers multiple advantages to healthcare that could improve the quality of patient care. By gathering patient information and analysing the data, healthcare professionals can detect patterns and anomalies that could indicate health risks. Generative AI can support clinical decision-making and encourage patients to take control of their health.
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