Quick Summary
AI transforms healthcare, impacting diagnosis, drug discovery, virtual health assistance, and medical and clinical solutions. This blog post explores AI’s applications, the problems it solves, and the trends to leverage. Keep reading to understand how AI in healthcare is worth your investment and promises massive ROI at a faster rate.
Table of Contents
1. Introduction
2. Application of AI in Healthcare
3. What Healthcare Problems Does Artificial Intelligence Resolve?
4. AI Technology Expertise & Trends to Leverage for Healthcare
5. The Future of AI For Healthcare Sectors
6. Conclusion
Introduction
Diagnosis and medical errors are major causes of deaths, and all due to time and technological constraints. An alarming number of 1 in every 10 patients and 3 million deaths occur per annum due to errors and unsafe care. That’s quite concerning.
But with AI in healthcare sector offering transformative services, tables have turned, and the margin of errors has gradually reduced. Besides, the healthcare sector using AI is expected to grow by 43%. It could breach the $2.9 billion market in 2022 to reach a new high of $51.3 billion by 2030. Therefore, entering the AI market now is advisable for healthcare providers, hospitals, pharmaceutical companies, or biotech companies.
This article is for healthcare entrepreneurs ready to ditch legacy-based systems and wholeheartedly welcome Artificial Intelligence. As an AI development company, we are prepared to provide AI-backed flawless solutions for your healthcare needs. So, let’s get started.
Application of AI in Healthcare
Artificial intelligence has paved the way for redefining the healthcare industry and empowering it with value-added resources. By exploring AI for healthcare use cases, we can better understand how artificial intelligence integration into healthcare will revolutionize the field.
AI for healthcare encompasses many applications transforming patient care, medical research, and healthcare administration. Below are the AI use in healthcare that you must know before deciding.
Applications of AI in Healthcare
Digital Health Monitoring
Let your patients rest in their homes and enable virtual consultancy with doctors. This refers to building a wide range of use cases with AI in healthcare, including HIPAA-compliant telemedicine software, mobile apps for patients and healthcare providers, wearables, patient-engagement chatbots, virtual nurses, appointment schedulers, and RPM systems with EHRs.
End-to-End Clinical Solutions
You might require experts in AI in the healthcare domain to build various healthcare-related end-to-end solutions, such as clinical trial management systems, electronic data capture systems, and patient engagement tools. Count on our AI developers for accurate clinical trial data analysis, eConsent, telehealth, and patient monitoring.
Drug Discovery
Statista says global spending on drug development R&D is estimated to be around 272 billion dollars in 2024. Therefore, now is the time to invest in AI-backed drug discovery platforms, clinical trial management, analysis, and customized software solutions.
Medicine Solutions
You must start building solutions focusing on Artificial intelligence in healthcare. AI helps healthcare professionals create customized medical treatments or diagnoses based on a patient’s genetics, lifestyle, and preferences.
Image Analysis Software
Another use of Artificial intelligence for healthcare is image analysis software which demands the utmost precision and attention. AI developers with advanced skills and proven expertise to build flawless and accuracy-delivering medical image analysis software. We can help you develop AI in radiology software for radiologists and healthcare professionals to diagnose diseases and plan treatment.
Medical Condition Forecasting
Another use case of AI for healthcare is building devices to forecast medical conditions. With the power of Artificial Intelligence (AI), medical condition forecasting is becoming a reality. This exciting field uses AI algorithms to analyze vast amounts of medical data that can identify patterns to predict the likelihood of developing certain diseases.
Robotic-assisted Surgery
Want to develop an AI-backed robotic-assisted surgery system for your hospital? But before that, you must know the possibilities of AI, such as robotic movement control systems, surgeon interface design and development, imaging data integration, and AI execution for innovative and safer medical procedures.
Personalized Treatment
You can even build AI-powered systems that provide personalized treatments, therapies, and diagnoses without side effects. Moreover, we have top-of-the-line expertise in developing customized real-time medical recommendations around the clock.
Readmission Risk Prediction
AI algorithms can analyze patient data to identify individuals at high risk of being readmitted to the hospital after discharge. This allows healthcare providers to implement targeted interventions, such as medication adjustments or follow-up care plans, to reduce readmission rates and improve patient outcomes.
Genomic Data Analysis
This AI application for healthcare brings innovation to the sector since the vast amount of information within our genes holds immense potential for personalized medicine. AI in medicine can analyze complex genomic data to identify genetic variations associated with specific diseases, allowing for earlier diagnosis, risk stratification, and development of more targeted therapies.
Rehabilitation Monitoring
AI-powered wearable devices and sensors can track a patient’s progress during rehabilitation. AI can analyze this data to assess recovery, identify potential complications, and personalize rehabilitation plans for faster and more effective recovery.
Clinical Trials Optimization
Clinical trials are crucial in drug development but can be expensive and time-consuming. AI in healthcare can analyze vast datasets to identify the most promising candidates for clinical trials, optimize trial design, and predict patient responses, leading to a more efficient and successful drug development process.
Chronic Disease Management
AI can analyze patient data, including medical history, medications, and lifestyle habits, to predict and prevent complications in patients with chronic conditions like diabetes or heart disease. This empowers patients to take proactive steps in managing their health and allows healthcare providers to deliver more personalized and preventative care.
