AI in Healthcare: Benefits and Examples
Artificial intelligence (AI) and machine learning (ML) in healthcare have already disrupted the industry, yet their full potential remains untapped. As technology advances, it will broaden AI in healthcare use cases, reducing costs and improving patient outcomes. AI is also proving to be a powerful ally for healthcare professionals, improving the precision and swiftness of disease identification and treatment recommendations by analyzing extensive patient datasets.
This technological support improves patient care and streamlines the diagnostic process. Moreover, AI's predictive analytics capabilities enable the forecasting of patient health, helping in proactive healthcare management and personalizing treatment plans. Remote monitoring, made possible by AI-driven wearables and systems, also allows continuous patient tracking, which is particularly valuable for chronic condition management.
AI in Healthcare in 2023 and 2024
As 2023 ends and we enter 2024, AI adoption in healthcare is steadily growing. A Morgan Stanley survey revealed that 94% of healthcare companies employ AI and ML in their operations. Data published by Statista states that the AI healthcare market, valued at $11 billion in 2021, is expected to reach $187 billion by 2030. Companies are pouring funds into AI and ML, with estimates by Morgan Stanley suggesting the average budget allocation to these technologies is set to grow from 5.7% to 10.5% from 2022 to 2024.
This growth, fueled by improved ML algorithms, increased data access, affordable hardware, and 5G, will reshape healthcare operations. The benefits of artificial intelligence in healthcare lie in its ability to analyze vast health data and rapidly identify subtle and complex patterns that would be too difficult for humans to detect. An increase in AI integration can also be partially attributed to the COVID-19 pandemic, which accelerated the digital transformation of the healthcare sector.
A leading nonprofit in the medical industry, Mayo Clinic has developed over 160 AI algorithms in cardiology, neurology, radiology, and other verticals to help improve patient care. As the healthcare sector embraces data-driven insights, AI is poised to revolutionize patient care and improve overall health outcomes.
The Benefits of AI in Healthcare Innovations
AI-powered healthcare delivery
AI and ML in healthcare can help increase diagnosis accuracy and reduce patient treatment costs, highlighting its significant impact on improving healthcare delivery. For instance, research published by the Healthcare Dive showed that using deep learning algorithms and AI in medical diagnosis accurately identified illnesses in 87% of instances. AI tools also offer healthcare providers more time for patient care and enhance risk coding, claims processing, and supply-chain management.
For patients, AI aids in treatment access and management, optimizing insurance channels, enhancing telehealth services, and disease detection.
Predictive care
AI algorithms and predictive analytics, apart from identifying the possibility of illnesses like the flu or hereditary conditions, can also help understand factors around us that can influence our health, including a person’s location of birth, diet, working environment, local air quality and access to a steady income, among other, to anticipate the development of chronic disease.
Predicting the possibility of an illness is paramount to help individuals take preventive measures before the condition worsens, proving to be extremely helpful in decreasing the number of cases of diabetes, heart failure, and COPD (chronic obstructive heart disease).
Genome Sequencing
Genomics, a branch of molecular biology, delves into the structure, function, and evolution of genomes or the genetic information in an organism. AI, ML, deep learning (DL), and natural language processing (NLP) have revolutionized genomic sequencing by identifying genetic variants in a human genome and collecting vast amounts of data. This advanced technology can help expedite scientific discoveries, aid genome assembly, identify variations, and guide drug development.
AI-supported genome sequencing can be used in sequencing critical-care patients with uncommon conditions or for genetics research. PacBio, one of the leading healthcare AI companies’ latest breakthroughs – the Revio system utilizes NVIDIA Tensor Core GPUs, providing a 20x boost in computing power compared to previous systems. This innovation allows accurate and scalable sequencing of human genomes with long reads for less than $1,000.
Healthcare AI Companies and Examples
Google Health: The tech giant has been a forerunner in developing advanced healthcare technologies. Google Health is involved in developing AI algorithms for medical imaging analysis to assist in interpreting X-rays, CT scans, and MRIs. The goal is to improve diagnostic accuracy and efficiency, benefiting healthcare providers and patients. Google also released Med-PaLM 2, its large language model, that can answer medical questions accurately, which can help medical practitioners in drafting responses, summarizing documents, and sharing learnings. Its DeepVariant initiative, an open-source variant caller that uses deep neural networks, has also proved successful in providing highly accurate genomic analysis to identify elevated risk for diseases like breast cancer.
Augmedix: A leader in medical documentation, Augmedix has developed solutions that extract and convert data from natural physician-patient conversations into real-time medical notes integrated with electronic health record (EHR) systems. This streamlines administrative tasks, potentially reducing burnout among healthcare professionals and increasing productivity. Their latest offering, "Augmedix prep," prepares patient notes and medical charts based on visit type and historical records, saving physicians time by providing relevant information in advance.
CloudMedX: Nestled in the heart of Silicon Valley, this startup is dedicated to enhancing patient and financial outcomes through predictive analytics. CloudMedX leverages natural language processing (NLP) and deep learning to extract data from electronic medical records, generating clinical insights for healthcare professionals to enhance patient results. The company's AI assistant supports doctors and patients in making informed, data-driven decisions. CloudMedx's solution has already demonstrated success in various medical domains, including congestive heart failure, liver cancer, ALS, renal failure, and orthopedic surgery. CloudMedx also received the "Best Overall Connected Healthcare Solution" at the 2019 GITEX Award.
Ethical and Regulatory Concerns Regarding the Use of AI in Healthcare
With rapidly evolving AI in healthcare projects that use sensitive patient data, the significance of ethics and regulations cannot be overstated. As these technologies become integral to medical practices, responsible and ethical AI implementation will be crucial to safeguard patient well-being, maintain privacy, ensure security, and foster trust. The World Health Organization (WHO) recently released a document to guide governments, developers, and regulators regarding the ethical use of AI in healthcare to address challenges the technology could impose.
Here are some ethical considerations when using AI technologies in healthcare:
Patient privacy and data security: Protecting patient data and ensuring compliance with privacy regulations (e.g., HIPAA, GDPR) are paramount in AI-driven healthcare to maintain patient trust and data security. Externally validating data and being transparent regarding the intended applications of the technology is essential.
Transparency: AI algorithms should be transparent and explainable to enable healthcare professionals to understand and trust AI-generated recommendations and decisions.
Bias mitigation: Strategies to identify and mitigate bias in AI algorithms are essential to ensure equitable healthcare outcomes for diverse patient populations. Ensuring high-quality data by rigorously checking systems before they launch and training systems on various data sets will be key in reducing bias and errors.
Ensuring accountability: In situations where AI technology malfunctions, such as when a tool's decision harms a patient, there should be established mechanisms to ascertain responsibility, involving identifying accountable parties like manufacturers and clinical users.
The Future of AI in Healthcare
The future of AI in healthcare can be categorized into three main areas: patient-oriented AI, clinician-oriented AI, and administrative- and operational-oriented AI. This encompasses various applications, from personal health management and virtual patient assistance to supporting healthcare professionals in complex decision-making. In the next decade, AI will leverage diverse data sources to uncover disease patterns, enhancing treatment and care. Predicting individual disease risks and recommending preventive measures will become a standard feature of healthcare systems. Furthermore, AI will play a key role in minimizing patient waiting times and enhancing overall efficiency in hospitals and health systems. Additionally, AI will continue to streamline administrative tasks and enhance operational efficiency.
The synergy between artificial intelligence (AI) and healthcare will transform the medical landscape, particularly in developing nations. Currently, in emerging economies like Africa, home to 15% of the world’s population, expenditure on healthcare is only 1%, as published by the Financial Times. AI and advanced technologies will be key in bridging the gap by aiding in swift and accurate disease diagnosis, facilitating access through telemedicine for remote consultations, reducing costs, and enhancing disease surveillance for early detection. Despite challenges around privacy and security around using AI in healthcare, the integration of the technology shows promise in making healthcare more accessible and efficient across the world, including resource-constrained regions.
Are you an organization or institution looking to drive new solutions with AI in healthcare?
Futurize can foster collaborations between academic institutions, governments, corporations, and startups to help you develop innovative ideas in healthtech. Get in touch with us at hello@futurize.studio!
