Transformative Applications of AI and ML in Personalized Treatment Pathways: Enhancing Rare Disease Support Through Advanced Neural Networks

Abstract

AI and machine learning have transformed various industries and public services. In the healthcare sector, its transformative potential is increasingly recognized. This essay focuses specifically on how advanced AI and machine learning with advanced neural networks could revolutionize and offer new solutions to treatment pathways for rare diseases. Many rare diseases are difficult to diagnose and treat. Early support and knowledge are limited, making the disease journey a tougher and more isolating experience. Support networks dedicated to specific rare diseases are even scarcer, as is research funding for such diseases. Recent trends show increasing interest and activity in cross-domain collaborations, which could impact both care pathways and supportive networks. The importance of early, more personalized and widened support is growing for rare disease individuals and their families. The essay will highlight different and innovative ways that personalized, advanced machine learning recommendations could strengthen the ecosystem of rare disease support. Applications, changing the way support individuals receive information and services, are discussed, as well as new data sources for support networks and advanced machine learning methods that enable the exploitation of these sources. As the burden of diseases is shifting and personalized approaches are becoming more viable, the importance of advancing from symptom-based to population and individual-based healthcare solutions is elevated. In addition to genetic analyses and biosensors, social media, internet browsing and smartphone usage are increasingly recognized as sources of health-related data. If used wisely and aligned with the appropriate non-disclosure agreements, these digital footprints could help healthcare providers to discover patterns of, e.g., triple negative breast cancer occurrences and offer timely recommendations to avoid certain factors. This essay discusses how advanced machine learning algorithms will revolutionize the way we can use these sources of data. A shift to personalized services that accommodate individual rare disease individuals’ needs and habits is further supported.