Wafik S. El-Deiry, MD, PhD, FACP

Books I have edited that may be of interest to those who study cancer. They are all available on Amazon.

@weldeiry @PubPeer @oncogenejournal We all thankful to @weldeiry for his ingenious work such as discovery p21/Waf1 and many others. Thank you , Wafik. Dying from my illness, I say "thank you"

Over two years of attacks, false accusations of fraud and misconduct led to reputation and career damage without justice. Sad to live through this experience after pursuing scientific truth, discoveries, government service, and helping patients with cancer. Definitely not what I expected when I chose the career of a physician-scientist 4 decades ago.

Jefferson to open Lehigh Valley medical school campus in Allentown bizjournals.com/philadelphia/n…

WIN Consortium - Exceptional Faculty of Global Leaders to Gather at Precision Oncology Symposium 2026 @WIN_Consortium @weldeiry @Dr_R_Kurzrock @AACRPres @curijoey oncodaily.com/voices/win-con…

Here's the current situation in VAERS for domestic data when querying "Aortic dissection". Not ONE report prior to 2020. And then... these are normalized rates per 100,000 annual reports. @Fynnderella1 @OpenVAERS @drdrew @delbigtree @brownstoneinst @Honest_Medicine @SenRonJohnson

Concerned about the future of science in America.

El-Deiry interview 7-9-26 with Real America's Voice (RAV) correspondent Ben Bergquam on July 9, 2026 at the Union League of Philadelphia. TOP CANCER RESEARCHER CALLS FOR COVID VACCINE TRANSPARENCY They discussed Dr. El-Deiry's testimony before the US Senate Permanent Subcommittee on Investigations June 3, 2026 hearing titled "Plausible Mechanisms of COVID-19 Injections Causing Cancer and Attacks on Scientific Publications and Research." The July 9, 2026 interview titled "TOP CANCER RESEARCHER CALLS FOR COVID VACCINE TRANSPARENCY" features Dr. Wafik El-Deiry who says Americans still don't have true informed consent for COVID mRNA vaccines, urging transparency, accountability, and open scientific debate instead of silencing questions. youtu.be/AXcQA6Fx_M8

@RealAmVoice @BenBergquam

TOP CANCER RESEARCHER CALLS FOR COVID VACCINE TRANSPARENCY Dr. Wafik El-Deiry says Americans still don't have true informed consent for COVID mRNA vaccines, urging transparency, accountability, and open scientific debate instead of silencing questions. @BenBergquam @weldeiry

A self-leveling electric stair climber moves 200kg without tipping.

@JanciToxDoc @RealAmVoice @BenBergquam Did anything come of this? downloads.regulations.gov/FDA-2025-P-180…

@RealAmVoice @BenBergquam @weldeiry At least there are some honest scientists left willing to tell the truth about this dangerous gene therapy technology masquerading as “vaccines”. Thank you Dr. El-Deiry!

Buying used books at an annual book sale in Barrington, RI is one of my favorite activities, even if someone comments on my Eagles T-shirt. I love all kinds of history including the local, science, travel and non-fiction. Will be back for more.

Nvidia CEO: Greatness does not come out of intelligence, it comes from character. Character is not formed out of smart people: it is formed out of people who have suffered.

A Stanford researcher named Fei-Fei Li once hired 49,000 strangers from 167 countries to look at pictures and answer one simple question, and their answers became the foundation modern AI is built on today. Back in 2006, Li was a freshly minted PhD from Caltech starting her first job as an assistant professor. Everyone around her was chasing the same idea, that the path to smarter AI ran through smarter algorithms. Better math. Cleverer code. She looked at the field and decided they had the problem backwards. A psychologist had once estimated that the average person can recognize about 30,000 different kinds of objects on sight. A dog. A very specific species of fern. Li's question was simple and almost embarrassing in hindsight. If a computer was ever going to see the world the way a person does, shouldn't it first be shown what the world actually looks like, at real scale, in all its variety? Nobody was building that. So she decided to build it herself. She moved to Princeton and pulled in a lexical database built by linguists there called WordNet, roughly 22,000 categories of nouns organized by meaning. That became the skeleton. Then came the impossible part. She needed millions of real photographs sorted correctly into every one of those categories, and there was no way she or her small team could label them all by hand. Working nonstop, one image a minute, with no sleep and no food, it would have taken one person almost 23 years. So she turned to Amazon Mechanical Turk, a website where you can pay strangers online to do small tasks for a few cents each. Over the next three years, those 49,000 workers in 167 countries looked at photograph after photograph and answered the same simple question, over and over. Does this picture show a dog. Does this picture show a fire truck. Each image got checked by multiple workers before it counted. By the time they were done, they had sorted more than 14 million images into over 20,000 categories. They called it ImageNet. When she finally brought it to the biggest computer vision conference in the world in 2009, the field shrugged. A hundred times bigger than any dataset that existed, and almost nobody cared. They didn't even give her a stage. They gave her a folding table in the corner of a convention center in Miami, wedged between a few posters nobody was reading. So Li did something clever. Instead of just publishing the data and hoping someone noticed, she turned it into a competition. Every year, teams would submit AI systems and see whose could recognize images most accurately against ImageNet. She built the incentive that the data alone could not create. For two years, nothing dramatic happened. Then in 2012, a team out of Toronto entered a neural network called AlexNet, trained on two ordinary gaming graphics cards. Every serious entry before it had an error rate hovering around 26 percent. AlexNet came in at 15.3 percent. An 11 point jump in a single year, inside a competition that used to inch forward by fractions of a point. That one result is the actual starting gun for the AI you use today. Not a lab announcement. Not a keynote. Just 49,000 strangers on the internet answering questions about photographs, three years before anyone realized what they had built.

Low- and middle-income countries are not just recipients of innovation—they are creating it. From context-appropriate screening & treatment strategies to AI-enabled multilingual health education, global conversations on equity deserve truly global representation 🙏 @somusp9

@WIN_Consortium @weldeiry Low- and middle-income countries are not just recipients of innovation—they are creating it. From context-appropriate screening & treatment strategies to AI-enabled multilingual health education, global conversations on equity deserve truly global representation 🙏 @somusp9

open.substack.com/pub/petermccul… @katiecouric

@RealAmVoice @deneenborelli @BenBergquam open.substack.com/pub/petermccul… @katiecouric