The global market for artificial intelligence in healthcare was valued at USD 15.4 billion in 2022 and is projected to grow at a compound annual growth rate (CAGR) of 37.5% from 2023 to 2030.
This growth is driven by several factors, including the increasing availability of patient health-related digital data, a growing demand for personalized medicine, and the need to reduce healthcare costs. Additionally, the aging global population, changes in lifestyle, and an increase in chronic diseases have contributed to a rise in demand for early disease diagnosis and improved understanding of diseases in their initial stages. Healthcare systems are increasingly adopting and integrating AI and machine learning algorithms to predict diseases accurately in their early stages based on historical health data.
Muteki Group have been transforming Healthcare solutions for different markets applying wide expertise in Artificial Intelligence and Machine Learning, Deep Learning and Neural Networks, Computer Vision and Speech Recognition
Where we can help
Precision medicine solutions
The combination of artificial intelligence (AI) and precision medicine has the potential to transform healthcare.
Precision medicine identifies patients with specific healthcare needs or uncommon treatment responses, while AI uses advanced computation to generate insights, facilitate learning, and enhance clinician decision-making
One of the most promising applications of AI is in expert systems, which are designed to replicate the decision-making capabilities of a human expert.
Expert systems can be used to analyze large amounts of data, identify patterns and trends, and provide insights and recommendations that can be used to improve business operations.
AI-powered expert systems
Medical Image Analysis with AI
Medical imaging plays a significant role in various clinical applications, including early detection, monitoring, diagnosis, and treatment evaluation of different medical conditions.
Artificial Intelligence (AI) and Machine Learning (ML) can be used in Radiography, endoscopy, CT, MG, Ultrasound images, MRI, MRA, Nuclear medicine imaging, PET, and pathological tests.
Remote Patient Monitoring (RPM) is a component of telehealth that enables more effective chronic patient management. Care teams receive and analyze a patient's physiological data regularly in real-time, outside of clinical settings, to provide more context about their disease condition.
RPM empowers care teams to receive alerts from vitals and non-compliance to medications or care plans to proactively engage with patients to improve outcomes.
Telemedicine and Remote Patient Monitoring
Clinical trial solutions
The utilization of AI in drug trials helps to improve the cost, clinical outcomes, and time required for drug trials.
AI-based solutions can help in different aspects of clinical trials such as drug trial design, patient enrichment & enrollment, investigator and site selection, patient monitoring, medication adherence, and many more, which is also boosting the growth of the market for AI-based clinical trial solution providers.
By using computational drug discovery software, researchers can save time and resources as they can quickly identify promising compounds and prioritize them for further testing and also get more comprehensive analysis of drug-target interactions.
Overall, the use of computational drug discovery software has the potential to revolutionize the pharmaceutical industry by accelerating the drug development process and improving the efficiency of scientific research.
Drug discovery and material design software