With the development of innovative tools such as ChatGPT, students in Chadwick International have been encouraged to explore ways of utilizing artificial intelligence to help them in their academic endeavors; many believe that AI algorithms show potential to revolutionize the education students receive. Experts say continued research and technological advancement can similarly have a significant impact on the medical industry, increasing human longevity for years to come.
By the year 2050, the world will witness a steep increase in cases of neurodegenerative disorders leading to drastic cognitive decline (Schependom). Diseases such as Alzheimer’s, Huntington’s, and Parkinson’s have been subjects of intensive research, but developing truly effective treatments remains a daunting task. A major challenge lies in diagnosing these diseases early, since significant neurological damage is already present by the time symptoms typically appear.
Robina Weermeijer, Figure of Brain, Unsplash, 6 Jun. 2019
Thus the medical community is turning to advanced computational techniques, including artificial intelligence (AI) and machine learning (ML) (ScienceDirect). These technologies can analyze extensive medical data, leading to improved diagnosis and treatment strategies for neurodegenerative disorders. AI has thus been utilized in medical diagnoses and prognoses since the 1970s through Clinical Decision Support Systems (CDSS). While early attempts faced limitations and failures, recent models like Large Language Models (LLMs) have shown revolutionary performance. AI’s use in genetic diagnostics enables specialists to identify genetic alterations that cause diseases, offering possibilities for future molecular interventions.
Early Diagnosis for Huntington’s Disease
Huntington’s disease, a rare and inherited condition that results in the progressive degeneration of nerve cells in the brain, primarily affects neurons in specific parts of the brain. The disease causes those neurons to gradually break down and die. It manifests as an array of symptoms, some of which include cognitive, motor, and emotional disturbances. With such a debilitating effect on those diagnosed, researchers are focused on finding methods to detect Huntington’s as early as possible. (Rey) Early detection is challenging and many studies have found only accuracy in detection postmortem.
Working with IBM and the CHDI Foundation, scientists recently developed an AI model outlining the progression of Huntington’s disease through its nine stages (Hale). By analyzing extensive datasets from observational trials like PREDICT-HD and TRACK-HD, the model provides a comprehensive understanding of Huntington’s disease progression, assisting in clinical trial design and biomarker identification, marking a significant stride in Huntington’s disease research (Molnar). Such models hold the potential for insights into other diseases like Alzheimer’s.
Continued Research For Technological Advancement
Various data types feed ML, deep learning models and medical AI technology, used to predict neurodegenerative diseases. However, concerns arise about the reliability of these ML predictions. To enhance the trustworthiness of AI diagnostics, researchers have integrated them with Explainable AI (XAI) frameworks (Research Square). XAI ensures that AI decisions are transparent and logical, especially in healthcare, where they tackle issues like long-term mortality predictions.
Aprinoia Therapeutics’ APN-1607 offers advanced PET tracers for these neurological diseases, enhancing diagnostics in and out of clinical trials and speeding up therapeutic evaluations (Buntz). Paul Tempest, the company’s head of medical chemistry, emphasizes the growing role of AI in their strategies, and global diagnoses, efficient administrative tasks, predictive analytics, and tailored treatments.
As a student witnessing the development of AI and its integration in the educational system, I acknowledge that the use of AI technology in the medical industry would not be without several risks. While advanced technology could create problems in schools regarding academic honesty and originality, issues in the medical industry could stem from its reliability. Yet in the same way that technological advancements can aid students and teachers greatly when utilized with caution, I believe artificial intelligence could benefit patients and doctors greatly. With increasing technological innovations, I hope we can look forward to a future where our ability to diagnose neurodegenerative diseases is greatly enhanced.
