therapeutic area

Kraft: Healthcare data-flow of the future will be fluid, proactive, and personalized


Dr. Daniel Kraft, a Stanford-educated MD who now serves as chair of medicine for Singularity University, a learning community founded by Ray Kurzweil and Peter Diamandis, sees himself as one of those leaders. Kraft will be sharing his observations, predictions, and advice at Health 2.0's Annual Fall Conference in two weeks in Santa Clara, California. "The bottom line is that for the last nine years I've had an interesting journey doing medicine for Singularity University and started this program called Exponential Medicine, which in its essence is that the future of health and medicine isn't digital, mobile, connected health, or AI," Kraft told MobiHealthNews. Click here to register for Health 2.0's Annual Fall Conference.]

A Solution to Missing Data: Imputation Using R


If the missing values are not MAR or MCAR then they fall into the third category of missing values known as Not Missing At Random, otherwise abbreviated as NMAR. The package provides four different methods to impute values with the default model being linear regression for continuous variables and logistic regression for categorical variables. In R, I will use the NHANES dataset (National Health and Nutrition Examination Survey data by the US National Center for Health Statistics). The NHANES data is a small dataset of 25 observations, each having 4 features - age, bmi, hypertension status and cholesterol level.

Deep Learning Prerequisites: Linear Regression in Python


This course teaches you about one popular technique used in machine learning, data science and statistics: linear regression. Linear regression is the simplest machine learning model you can learn, yet there is so much depth that you'll be returning to it for years to come. We will apply multi-dimensional linear regression to predicting a patient's systolic blood pressure given their age and weight. If you want more than just a superficial look at machine learning models, this course is for you.

Doctor Hazel, an AI aimed at skin cancer detection, is latest in a long line


Engineers participating in a hackathon last weekend demonstrated an artificial intelligence that they say could someday detect cancerous moles, TechCrunch reports. Apps, mobile platforms, and camera devices designed to evaluate moles and estimate skin cancer risk have a long history filled with successes and failures. That same year, University of Michigan Health System physicians launched UMSkinCheck featuring reminders and instructions for patients to self-examine their moles and skin lesions over time. The FTC alleged that the marketers of both mole photography-based apps "deceptively claimed the apps accurately analyzed melanoma risk," and that the marketers had insufficient evidence to make these claims.

Forget Police Sketches: Researchers Perfectly Reconstruct Faces by Reading Brainwaves


Using brain scans and direct neuron recording from macaque monkeys, the team found specialized "face patches" that respond to specific combinations of facial features. In the early 2000s, while recording from epilepsy patients with electrodes implanted into their brains, Quian Quiroga and colleagues found that face cells are particularly picky. In a stroke of luck, Tsao and team blew open the "black box" of facial recognition while working on a different problem: how to describe a face mathematically, with a matrix of numbers. In macaque monkeys with electrodes implanted into their brains, the team recorded from three "face patches"--brain areas that respond especially to faces--while showing the monkeys the computer-generated faces.

Artificial Human Embryos Are Coming, and No One Knows How to Handle Them

MIT Technology Review

Two years ago, Shao, a mechanical engineer with a flair for biology, was working with embryonic stem cells, the kind derived from human embryos able to form any cell type. The work in Michigan is part of a larger boom in organoid research--scientists are using stem cells to create clumps of cells that increasingly resemble bits of brain, lungs, or intestine (see "10 Breakthrough Technologies: Brain Organoids"). Scientists have started seeking ways to coax stem cells to form more complicated, organized tissues, called organoids. Following guidelines promulgated last year by Kimmelman's international stem-cell society, Fu's team destroys the cells just five days after they're made.

Writing family stories: Jason Tougaw on his memoir 'The One You Get'

Los Angeles Times

Tougaw guides us into realms of fascinating scientific inquiry, places like dream theory, neuroscience, and cutting-edge theories of consciousness, places that ultimately illuminate what it was to be him, but more, what it is to be human. When I was a teenager, I got obsessed with Jean Cocteau (by way of a David Sylvian song). I'll admit that revenge probably did motivate me in some ways to write the book, but I didn't think about the neuroscience that way, until I wrote that line about Stanley, which was sort of a joke to myself. David Sylvian wrote songs inspired by Jean Cocteau.

3 Ways AI Is Changing Medicine @themotleyfool #stocks $IBM, $PFE, $GOOGL, $NVDA, $GOOG


Companies like Alphabet Inc. (NASDAQ:GOOGL) (NASDAQ:GOOG), International Business Machines (NYSE:IBM), and NVIDIA Corporation (NASDAQ:NVDA) are using the predictive power of AI to provide doctors with additional tools to fight disease. Researchers at Alphabet's Google Brain have developed an AI system that can examine images of the retina and detect DR as well as human ophthalmologists, according to a paper published in the Journal of the American Medical Association. HeartFlow is medical technology company that is using graphics processors from NVIDIA Corporation (NASDAQ:NVDA) and deep learning to create 3D mapping used to provide early detection of heart disease. The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), and Nvidia.

The world is definitely going to end — just probably not Saturday


Musk worries AI could start World World III and Hawking worries "the development of full artificial intelligence could spell the end of the human race." "Once humans develop artificial intelligence, it will take off on its own and redesign itself at an ever-increasing rate," Hawking told the BBC. "I was a member of the NASA Advisory Council on Planetary Defense which studied ways for NASA to defend the planet from asteroids and comets," NASA aerospace engineer Brian Wilcox told the BBC. "I came to the conclusion during that study that the supervolcano threat is substantially greater than the asteroid or comet threat."