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4 Ways in which AI is Changing Healthcare

4 Ways in which AI is Changing Healthcare Blog Post

It’s impossible to read the news these days without coming across multiple articles about artificial intelligence (AI) and how it is going to revolutionize our social and economic systems. In healthcare, AI is poised to transform the delivery of services – promising improved efficiency, accuracy, and accessibility. Here are four ways in which AI may shape the future of healthcare delivery in the US.

1.Enhanced diagnostics and personalized therapies

AI-driven diagnostic tools have the potential to improve the accuracy and efficiency of disease detection. Machine learning (ML) algorithms can analyze vast amounts of data to identify patterns and predict diseases at earlier stages, leading to timely interventions and better patient outcomes. Just one example is J&J’s Monarch™ Platform, which leverages AI and ML algorithms to enhance physicians’ ability to locate potential tumors during bronchoscopy procedures, leading to more appropriate diagnosis and treatment of lung cancers. 

AI can also enable personalized treatment approaches by analyzing genetic data and tailoring therapies to individual patients, thereby optimizing treatment efficacy and minimizing adverse effects. At Cedars-Sinai Center for Surgical Innovation and Engineering, Joseph Schwab, MD and his team use AI to make predictions for use in clinical practice, such as interpreting electronic health data. For example, a patient may be considering a procedure that has a 5% complication risk for the overall population. However, using AI to interpret their personal health information may show that the patient’s individual risk of complications is closer to 25%. This approach could significantly impact decision-making.

2. Remote monitoring and telemedicine

AI-driven remote monitoring technologies have the ability to continuously monitor patients' health outside of traditional healthcare settings. AI-driven wearable devices, such as smart watches, can track vital signs, detect irregularities, and alert healthcare providers, which can facilitate more proactive management of chronic conditions. 

Eko, a California-based company famous for its digital stethoscopes, has an AI-enabled system of heart monitors, patient and HCP software, and sophisticated reporting. Their platform helps identify early signs of atrial fibrillation and structural heart disease, and shares actionable data with the patient’s physician. In addition, telemedicine platforms powered by AI can facilitate remote consultations, enable patients to access services, improve outcomes, and reduce the burden on the healthcare system.

3. Precision medicine and drug discovery

AI has the ability to advance precision medicine by analyzing large-scale clinical and genomic databases to identify biomarkers, predict drug responses, and develop targeted therapies. ML algorithms can expedite the drug discovery process by simulating molecular interactions, predicting compound properties, and identifying potential drug candidates with higher success rates than traditional methods. 

AI can accelerate the pace of drug development and enhance the likelihood of discovering breakthrough treatments. For example, Innoplexus has developed an AI platform that collects large quantities of data from research and publications. The tool can help companies predict the outcome of clinical trials, and in fact, anticipated that a new therapy in development by a biopharmaceutical company for Alzheimer’s disease would fail with 70–90% certainty. The trial did fail, which reduced the company's market value by almost a third.

4. Clinical trial acceleration

Utilizing AI can also be extremely helpful in the recruitment process of clinical trials. By applying AI and ML algorithms to large patient datasets, researchers are able to identify and locate clinical trial sites with patients who may benefit the most from new therapies. This method also encourages the identification of a broad spectrum of patients, which is critical to ensure treatments are being studied in diverse patient populations that are representative of the disease.  

Although it has the capacity to transform healthcare, AI does carry with it certain challenges, such as regulatory hurdles and data privacy concerns. According to a recent article in FiercePharma, approximately 65% of the top-20 pharmaceutical manufacturers have banned the use of ChatGPT due to concerns about the loss of sensitive internal data to competitors. Stakeholders will need to work together to leverage the benefits of AI, while minimizing its potential problems. 

By harnessing the power of AI-driven technologies, healthcare stakeholders can facilitate a more efficient and accessible healthcare system that can meet our evolving needs. At SAKS Health, we look forward to supporting clients who are trying to bring breakthrough innovations to the healthcare ecosystem. Across our multiple practice areas, we will be closely monitoring developments in AI that help advance us towards Better Healthcare Tomorrow™.



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