The nuances of vaccines: comparisons to artificial intelligence in healthcare

“Vaccines don’t save lives. Vaccination programs save lives. ” David Paltiel, professor at Yale School of Public Health In the midst of the raging COVID-19 pandemic with its deadly apocalypse of well over 1 million deaths worldwide, there is now a glimmer of hope with at least three vaccines (Pfizer

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Development and Verification of a Digital Twin Patient Model to Predict Specific Treatment Response During the First 24 Hours of Sepsis Lal, Amos MBBS; Li, Guangxi MD; Cubro, Edin MSc, MBA; Chalmers, Sarah MD; Li, Heyi MD; Herasevich, Vitaly MD, PhD, FCCM; Dong, Yue MD; Pickering, Brian W. MB, BAO,

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The conundrum of evaluation metrics: accuracy, roc vs pr auc, and f1 score

“In the depth of winter, I finally learned that there was in me an invincible summer. ” Albert Camus, French author of The Plague In our past newsletters, we had covered important topics in data science such as the imbalanced dataset and parameters vs hyperparameters. As the COVID-19 pandemic rages

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Parameters and hyperparameters: a conundrum in machine and deep learning

“Be confused. It is where you begin to learn new things.” S.C. Lourie, British writer As we plan for the upcoming inaugural comprehensive review course for the nascent American Board of Artificial Intelligence in Medicine and its certification assessment, several topics appear to be conundra for esp

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Intelligence-based medicine: What I've learnt after reviewing 70 manuscripts!

“Maybe that’s enlightenment enough: to know that there is no final resting place of the mind; no moment of smug clarity. Perhaps wisdom… is realizing how small I am, and unwise, and how far I have yet to go.” Anthony Bourdaine American cook/author and global traveler We have remained in a viral apoc

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The Top 10 mistakes healthcare executives make with AI

“Some executives think that artificial intelligence is a sentient being, but it is simply a better way to turn data into actionable insights.“ Ryan Detert, CEO Influential Artificial intelligence (AI), with its machine and deep learning, natural language processing, and robotic process automation to

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The role of Bayes theorem in testing for COVID-19 (Part 2)

“Humans, it turns out, are not very good at Bayesian inference, at least when verbal reasoning is involved. The problem is that we tend to neglect the cause’s prior probability. ” Pedro Domingos, in The Master Algorithm We remain in the most challenging global health crisis of our generation, with t

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