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Considering estimations predict that AI in the global healthcare market will reach $194.4 billion by 2030, it is clear that AI (artificial intelligence) is an increasingly crucial tool for the future of healthcare. CSOFT has written extensively on AI in our AI Communications series which recently discussed how the first quantum natural language processing (QNLP) toolkit is increasing NLP (natural language processing) capabilities, and how linguistic AI is advancing real-world applications in areas such as machine translations (MT). In a recent CSOFT Health Sciences blog we explored how AI in healthcare is enabling the expansion of treatments to patients suffering with mental health illnesses and to patients diagnosed with diabetes. AI, through use of smart technologies can simulate human intelligence and is used in a wide range of disciplines, including in biology, computer science, mathematics, engineering, psychology, and more. But how has AI’s capabilities generated so much growth and excitement in the healthcare industry?

More and more, healthcare providers are reaping the benefits of AI as it facilitates improved patient care and clinical management tasks. Most often, AI is used as a diagnostic tool for treatment, but it is also used in personalized medication, drug development, and in patient monitoring. As more and more practices are informed and directed by the collection of healthcare and patient data, and as this data becomes progressively more complex, the rise of AI will continue to drive greater patient outcomes.

As a form of AI, through machine learning technology, providers are also able to analyze large amounts of computer records, medical data, and algorithms (such as deep learning, querying methods, and context aware processing) to identify disease patterns and patients’ current health situations. Machine learning will be key to incorporating and applying other technologies like surgical robotic tools, CAT scans, MRIs, virtual nursing assistants, administrative workflow assistance, and dosage error reduction, that can enable clinical professionals to use targeted methods to improve productivity and medical precision. The COVID-19 pandemic has also fueled this adoption, given the higher demand for decentralized, hybrid or remote clinical trials and patient research. In this way, AI will be essential to providing accurate patient care, especially through telehealth and remote patient monitoring.

As mentioned above, CSOFT has explored the abilities and advantages of natural language processing (NLP), an established technology with a wide range of real-world applications, in past blogs. As a subgroup of computer science, linguistics and AI, NLP technology enables computers to process human language via text or voice recordings to capture large volumes of text in real time. NLP is also a key technology that will enable providers to facilitate patient care and communication more effectively and efficiently. As our blog titled, Language AI in the News: The World’s Largest and Most Capable Language AI System to Date, notes, this advancement in the AI sector should be seen as a positive one and one that can be used alongside human translators rather than as a replacement. This is particularly important as it will ensure the continued support of medical translation and medical interpreting for patients seeking treatment or diagnostic care in their preferred language.

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