Useful Applications of AI for Medical Advancement
Published Date: 05/20/2023 Author: Dora Xu
As applications of AI have expanded to a variety of different fields such as in education, transportation, and manufacturing, there is a lot of potential for innovation, particularly in the area of medicine. Although the most common applications of AI are seen in the forms of web searches, content recommendations, targeted advertising, and autonomous vehicles, artificial intelligence also includes a variety of medical applications such as diagnosing patients, drug discovery and development, transcribing medical documents, and remotely treating patients. Further enhancements of these applications will be necessary to drive the future of medicine and promote progress in the healthcare industry.
Several significant strides have been made in finding ways to incorporate AI into medical processes. For example, in the field of visually oriented specialties, such as dermatology, clinical imaging has been used to develop classification models that aid physicians in diagnosing skin cancer, skin lesions, and psoriasis. Specifically, Dr. Esteva trained a deep convolutional neural network (DCNN) model using 129,450 images to categorize them as either keratinocyte carcinoma or seborrheic keratosis; and either malignant or benign. The results found that DCNN performed at par with 21 board-certified dermatologists. This success shows that using an AI model has many advantages including increased diagnostic efficiency, detection at earlier stages, vast coverage of screening programs reducing barriers to access, and the opportunity to receive a second opinion.
Besides the process of diagnosis, AI systems have also helped with drug discovery and personalized treatment options. Companies such as Verge Genomics use machine-learning algorithms to analyze human genomic data and identify drugs that can help treat neurological diseases such as Parkinson’s in a cost-effective way. Additionally, the growing popularity of AI assistants has been able to enhance patient experience, patient care, and provide support to physicians. Companies including BotMD have built systems that handle 24 hour clinical needs. In particular, they can track which physicians are on call and schedule the next available appointment, answer prescription related questions, and help doctors search hospital protocol and lists of medications or tools all through a mobile app to improve workflow.
Overall, it seems that AI has already revolutionized various aspects of the healthcare industry, whether by improving patient diagnosis, contributing to more personalized care, or increasing the efficiency of administrative duties. Although AI does still present several limitations such as issues with biased data, ethical concerns in the case of an inaccurate algorithm, or information privacy, AI systems have still undoubtedly made significant contributions to medical research and patient care. In order to better integrate AI into healthcare and see even more innovation, more data is necessary. Without radical changes such as completely digitized medical records, standardization of data infrastructure, and stronger management regarding confidentiality and consent, it will be impossible to make further strides in the future of AI-based medicine.
