Advertisement
X

Improving Patient Outcomes Through Artificial Intelligence: Personalized Medicine

One of the major aims of the Patient protection and Affordable Care Act is to improve value, quality, and efficiency in the delivery of healthcare services while minimizing costs and increasing the accountability of the healthcare system to a diverse patient population

One of the major aims of the Patient protection and Affordable Care Act is to improve value, quality, and efficiency in the delivery of healthcare services while minimizing costs and increasing the accountability of the healthcare system to a diverse patient population.

The realization of this aim largely depends on the ability to address the unique patient needs through personalized medicine, also referred to as precision medicine.Healthcare professionals are expected to take into account the unique needs, circumstances, and characteristics of patients and focus on the delivery of treatments, preventive measures, and medical interventions that closely align with individual preferences and needs.

Personalized medicine promises to significantly improve patient outcomes, mitigate diverse effects, optimize healthcare effectiveness, and enhance overall wellness. However, the success of personalized medicine depends on the ability to collect, process, analyze, and store large volumes of data about the needs, preferences, and health conditions of patients to inform the identification of patterns and generation of insights that support diagnosis, selection of treatments, and prognosis.

Artificial intelligence is an invaluable companion for healthcare professionals concerned with the delivery of personalized healthcare services.

Dr. Abdul Sajid Mohammed is a Senior Engineer and a Cloud Solutions expert leading a critical role at Microsoft Corporation where he contributes his skills and knowledge to one of the leading software technologies development organizations in the world.

He is an esteemed Research scholar boasting over 14+ years of expertise wherehe has accomplished many demanding targets, and led and executed many multi-million-dollar business-critical projects for some distinguished companies in the domains of AI Machine Learning, Big Data, Healthcare, and Cloud Computing.

Mohammed has also earned a Ph.D. in Information Technologyfrom The University of The Cumberlands, with a specialized focus on Artificial Intelligence-induced Machine Learning models and Big Data Analytics.Beyond his proficiency in IT, Abdul demonstrates a profound passion for the fields of healthcare and medicine.Dr. Mohammed's impactful research, particularly in the development of AI-induced machine learning models, has been published in distinguished journals, earning him numerous accolades for his exemplary contributions.

As a component of computer science, artificial intelligence is concerned with the design and development of intelligent machines that are capable of behaving intelligently like humans.

These systems are capable of understanding complex situations, simulating the thinking and reasoning process of humans, and solving sophisticated problems. Advances in AI have extended its application to health care and biomedical sciences to leverage the power of advanced algorithms to carry out intelligent tasks, such as the analysis of large volumes of data. An important contribution made by AI in the area of personalized medicine is enabling the collection, storage, normalization, and tracing of patient data.

Advertisement

AI algorithms are increasingly employed in the analysis of medical data, such as electronic health records, medical images, and genomic information. These algorithms have been successfully used to interpret medical images, including magnetic resonance imaging (MRIs), computed tomography (CT), and X-rays thanks to the ability to efficiently analyze humongous amounts of imaging data while simultaneously discovering patterns and abnormalities that would otherwise not have been detected by the human eye. The application of AI algorithms reduces the number of false negatives and false positives in the diagnosis of lung cancer, which leads to increased accuracy in the detection of cancerous nodules.

One of the areas of precision medicine that have been revolutionized by AI is the diagnosis and stratification of patients. AI algorithms are capable of analyzing sophisticated medical records to enable the accurate diagnosis of diseases and categorization of patients into various groups to allow the development of targeted treatments for every patient group.

Advertisement

The second is the prediction of the response to treatments. AI allows the analysis of past medical data to enable the prediction of the response of patients to various treatments and interventions, allowing the discovery of the most effective treatment for specific patients while improving overall wellbeing.

Third, the application of AI in precision medicine enhances the discovery and development of drugs by enabling the discovery of suitable drug candidates and prediction of the efficacy of drugs in addressing various diseases. This leads to accelerate discovery of personalized drugs while reducing the cost and time involved in traditional approaches to drug discovery.

Finally, AI supports the discovery of novel biomarkers, including proteins, genes, and other molecular indicators that play a fundamental role in the timely detection and prognosis of diseases to allow personalized treatments. AI algorithms are capable of uncovering patterns that would otherwise not be recognized. The identification of new biomarkers enables medical practitioners to better understand disease mechanisms and identify the most appropriate patients for various treatments.

Advertisement

It is evident that AI continues to revolutionize the area of precision medicine. Future researchers may focus on the impact of other Industry 4.0 technologies on precision medicine. These technologies include the Internet of Things (IoT), cloud computing, and blockchain technology. Each of these technologies has a profound impact on precision medicine. The integration of these technologies to support precision medicine will significantly improve patient outcomes.

Show comments
US