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Leading the Way in Effective Drug Development

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Jun 14, 2022

From Predicting Adherence to Health Outcomes – The Power of Predictive Insights

Clinical researchers have begun adopting predictive analytics to anticipate a patient’s engagement in a clinical trial, including if and how a patient will adhere to their treatment plan. As these models are fed more patient-level audio and visual data, they have the potential to open up a whole new world of a patient’s lived experience – from how a patient will respond to their medication, to the likelihood of developing side effects, to the broader trajectory of their disease.

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Jun 08, 2022

Closing the Gender Gap in STEM Careers: The Role of Networks, Authenticity & Leadership

Since AiCure was founded, diversity has been a grounding principle in all that we do – from diversity in our datasets, to diversity in the team behind our solutions. Early on, we realized opening our doors to diverse perspectives and investing in their fulfillment means we can build products that are more inclusive for their customers and create a workplace that best suits the needs of all employees.

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Jun 01, 2022

Big, Small & Wide: Combining Old and New Data Approaches to Advance Precision Medicine

For decades, data scientists and AI developers have typically followed the belief that “bigger is better” – the bigger the data set, the more analytical freedoms one has, and the more insights one gains. The AI industry still heavily relies on big data analytics, and for good reason – we need to feed AI large amounts of high quality, diverse data to ensure it works effectively for its intended patient population.

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Apr 26, 2022

Open-Source AI Platforms: Driving Success through Diversity

Digital biomarkers can open a world of possibilities in understanding the nuances of a patient’s behavior and response to treatment. Rather than relying on subjective perceptions of how a patient is responding, digital biomarkers treat patient observation more like an engineering problem.

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Apr 13, 2022

Why open-source AI platforms are the future of patient health tracking in clinical trials

Imagine you’ve just been diagnosed with cancer and you’re enrolled in a clinical trial for a promising new drug. You notice that after chemotherapy you struggle with occasional fatigue. Yet, whenever you visit your doctor every couple of weeks, you feel fine. This is not only a frustrating experience for patients, but it can also compromise the safety data in a clinical trial.

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Mar 24, 2022

From Black Box to Transparency: Pulling the Curtain Back on Machine Learning

The introduction of Good Machine Learning Practices (GMLP) and increasing buzz around the need for transparency and standardization of machine learning (ML) are significant steps to encourage adoption and trust in these tools across the healthcare industry.