AI techniques Archives - Healthentia https://healthentia.com/tag/ai-techniques/ Thu, 30 May 2024 11:22:30 +0000 en-US hourly 1 https://healthentia.com/wp-content/uploads/2020/04/cropped-favicon_512-32x32.png AI techniques Archives - Healthentia https://healthentia.com/tag/ai-techniques/ 32 32 193384636 iHelp https://healthentia.com/ihelp-study/ Tue, 04 Jan 2022 13:17:52 +0000 https://healthentia.com/?p=19053 Study Details Type: Research Disease: Pancreatic Cancer Sites: European countries Start: January 2021 Population: 420 patients Duration: 36 months Study Description iHelp is a research study that delivers a novel personalised-healthcare framework. Enables the collection, integration, and management of health-related data from various sources (medical records, lifestyle, behaviours, social media interactions). The data is analysed...

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Study Details

  • Type: Research
  • Disease: Pancreatic Cancer
  • Sites: European countries
  • Start: January 2021
  • Population: 420 patients
  • Duration: 36 months

Study Description

iHelp is a research study that delivers a novel personalised-healthcare framework. Enables the collection, integration, and management of health-related data from various sources (medical records, lifestyle, behaviours, social media interactions). The data is analysed using advanced AI techniques to draw adaptive learning models that are used to provide decision support in the form of early risk predictions as well as personalised prevention & intervention measures (alerts, behavioural nudges, consultations medications, therapies, screening, etc.) that are delivered through user-centric mobile and wearable applications.

Study Design & Method

Patients will receive a state-of -the-art wearable device (i.e monitoring bracelet) that will collect at a daily basis Real-World Data like activity (i.e. steps per day), sleep, and vital signs. The collected data are then transferred to the patient’s paired device through the Healthentia application downloaded on their smartphone. 

During the whole observation period, patients will be also asked to report their weekly wellbeing through the same application, completing dedicated questionnaires. Patient-reported outcomes together with the data coming from the wearable device are used to create lifestyle behavioral patterns of patients utilizing AI algorithms for understanding patients' habits and connections. 

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Determine key risks associated with Pancreatic Cancer

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Develop predictive models for identified risks

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Develop adaptive models for targeted prevention and intervention measures

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