# Smart healthcare - [Smart healthcare](#smart-healthcare) - [Intro](#intro) - [Reasons](#reasons) - [Implementation](#implementation) - [Research: data driven health accessment](#research-data-driven-health-accessment) - [Background](#background) - [Data](#data) - [Wearables](#wearables) - [Patient Health Records](#patient-health-records) - [Structured vs. unstructured](#structured-vs-unstructured) - [Smart digital health platform](#smart-digital-health-platform) - [Diagram](#diagram) - [Use Cases](#use-cases) - [Conclusion](#conclusion) ## Intro - History: ![history](./assets/5-smart-health-history.webp) - Patient centric - Precision medicine - Atrial digital twins ## Reasons - Current problems: - Global Health Disparities - Unequal shortage of healthcare workers - Increasing rate of burnout in healthcare - Mental health - Sustainable Development Goal 3 - What smart healthcare can help - Remote doctor consult - Reduce un-necessary hospital visits - Democratize healthcare access - Remote emergency - 5G powered emergency channel give doctor real time view - Real time access of vital signs like ECG, ultrasound image, and blood pressure - Access to medical history - Doctors guide paramedics in ambulance - Drug discovery - Cost saving and agility methods - All fancy words including (ML, DL, ANN) - Offset a shortage of specialists - AI can help in aiding diagnosis - Before smart hospitals - Data presented is overwhelming - hindering the ability of using it effectively - People trip and die in hospitals - Too much administration work - Shortage of qualified staff - Spending wasted in managing assets - Nurses waste time in searching for medical equipment - Benefits of smart hospitals - Save money on asset searching - Reminder - Home-based health monitoring reduces re-admission - Eliminate emergency - Warning of deterioration ## Implementation - EMR: Electronic medical records - Diagnosis, Image Data, Unstructured text data, Medications, Procedures, Lab tests - Data is challenging to use: high dimensionality, sparse, noisy, irregular, biased - IoMT: lots of data, lots of money going in - Healthcare technology: Better quality of life, with less money required - ![stupid diagram](./assets/5-smart-health-benefit.webp) ## Research: data driven health accessment ### Background - Role of AI - Detection of aliment - Improve decision making - Help in treatment - Superior experience - Tech revolution - Automated steps in diagnostic process - Can acquire different types of data, representing the physiology of humans - Images: MRI, CT - Wearable devices - Electronic health records - Robotics - ML learn from data, so that it can make decisions like human brain ### Data #### Wearables - Versatile monitoring #### Patient Health Records - Personal demographics: age, gender, ethnicity, weight, height, BMI - Medical parameters: blood, pressure, fat, blood sugar, plasma - Non-medical parameters: physical activity, diet plan - Questionnaires filled - Text mining can be performed #### Structured vs. unstructured - Structured: Time, date and code in diagnosis logs, can be stored in RDBMS - Semi-structured: medication taken, procedures, allergic reactions - Unstructured: Clinical notes, need NLP tools ### Smart digital health platform #### Diagram ![stuff](./assets/5-smart-health-platform.webp) #### Use Cases - Heart disease detection - Computer aided retinal disease diagnosis ### Conclusion - Future of healthcare technology involves: - Self monitoring - AI for health management - Research is being developed to integrate real-time data with technology - Require future clinical trails - Explainable artificial intelligence: - Need model transparency for clinicians and stakeholders - Need collaboration in all fields: - Academics - Clinicians - Industries - Stakeholders