“The ability of a machine to perform cognitive tasks to achieve a particular goal based on provided data” is the definition of artificial intelligence (AI). Global healthcare systems are being revolutionized and reshaped by this new strategy. Medical imaging diagnosis and assessment are being transformed by the ever-increasing computational power of AI’s highly developed and clinically relevant algorithms combined with sophisticated image processing software. This combined power enables the ‘cognitive’ computer to do tasks that human clinicians, regardless of skill and training, would be unable to perform, including scanning billions of pieces of unstructured data, extracting pertinent information, and recognizing complex patterns with increasing confidence through mass iterative learning.
Using AI-powered personalised medication can result in more effective treatment of common conditions such as heart disease and cancer, or rare diseases such as cystic fibrosis. Instead of using the current criteria of age and sex, it could enable clinicians to assess patients based on their unique health profiles or to optimize the dosage and timing of medication for each patient. This AI-personalised approach can help in early diagnosis, prevention, and better treatment thus, saving lives and making better utilisation of resources.
How can AI be used for personalized healthcare?
- AI for diagnosis and treatment:
Helping doctors diagnose and treat patients based on their unique symptoms, medical history, genetic profile, and lifestyle factors is one of the primary uses of AI in personalized care. Artificial Intelligence (AI) has the capability to examine vast volumes of data from multiple sources, including genomic sequencing, wearables, lab testing, imaging scans, and electronic health records. This analysis can produce insights and suggestions that can aid in clinical decision-making. AI is useful in identifying rare diseases, forecasting disease progression, recommending the right dosage for medications, and tracking the effectiveness of treatments.
- AI for prevention and wellness:
By offering individualized feedback, direction, and support, AI can also help patients prevent and manage chronic illnesses like diabetes, heart disease, and mental health problems. AI is able to follow and evaluate each patient’s health condition, activity, and risk factors using data from sensors, apps, and online platforms. It can also provide customized therapies that can enhance each patient’s health and well-being. AI has the ability to assist patients in a number of ways, such as goal-setting and achievement, medicine remembrance, healthy habit coaching, and problem detection.
- AI for education and engagement:
Educating patients about their health and encouraging greater patient participation is another method AI might facilitate individualized care. AI can offer patients pertinent and easily accessed information, respond to their inquiries, and allay their worries by utilizing conversational agents and natural language processing. In order to encourage and thank patients for their engagement and adherence, AI can also leverage gamification, personalization, and social aspects. AI, for instance, can link patients with peers and healthcare professionals, offer them engaging and entertaining learning opportunities, and assist patients in understanding their diagnosis, available treatments, and expected results.
- AI for research and innovation:
Helping researchers and innovators find new information and ideas that can improve healthcare and benefit patients is a fourth way AI can enable individualized care. AI can find patterns, trends, and relationships that can lead to new ideas and hypotheses by using data mining, machine learning, and simulation. AI can also be used to create and test new concepts and products that can raise the standard and effectiveness of healthcare through optimization, synthesis, and design. AI, for instance, can assist researchers in finding novel biomarkers, therapeutic targets, and devices, as well as assist entrepreneurs in developing new platforms, apps, and gadgets.
- AI for ethics and policy:
Helping to resolve the moral and legal issues raised by the application of AI in healthcare is a fifth method that AI can facilitate individualized care. In order to assess the moral and social ramifications of AI applications and to make sure that they are just, open, accountable, and respectful of human rights and dignity, AI can make use of logic, reasoning, and values. AI can also be used to inform and influence the creation and application of laws and policies that can promote the ethical and safe application of AI in healthcare through lobbying, analysis, and evidence. AI, for instance, can assist in evaluating the advantages and disadvantages of AI applications, identifying and reducing potential biases and harms, and encouraging patient and stakeholder participation and empowerment.
Applications of AI-based tools for disease treatment
- Autism Spectrum Disorder (ASD), a growing concern, cannot be cured using drugs, hence the treatments administered mainly aim to reduce the symptoms induced by the disorder. However, diagnosis and related treatments in terms of improving communication, social and behavioural skills are very challenging due to the heterogeneity of the disorder. Although recent development in artificial intelligence (AI) and machine learning (ML) techniques, ASD can now be detected at an early age and help provide personalised behavioural treatment to patients.
- AI tools are also being developed for use in cancer treatment. CURATE.AI platform (software) recommends drug dose in accordance to the clinical data obtained. CURATE.AI has opened up the possibility of personalised dosing for single- and multi-drug regimens, that is dynamically optimized throughout treatment. Furthermore, it is based on a small data set collected only from the treated individual rather than population data thus, overcoming the challenges that impede the adoption of big data approaches for personalised drug dosing. The Health Sciences Authority in Singapore classified CURATE.AI as a Class B medical device (low to moderate risk), which is defined as all active therapeutic devices that are software, or which are intended to administer or exchange energy to or with the human body.
- AI can also be used in diabetes treatment by image analysis (retinopathy, other applications), clinician DSS (complications prediction, diagnostic support, personalised treatment); automated retinal screening; and patient self-management tools (education and support, and insulin and glucose management) mainly focusing on glucose sensors and closed-loop technology.
Vaishnavi Shitole
Final Year B. Pharmacy