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A Smart Stethoscope Puts AI in Medics’ Ears

Engineers from Johns Hopkins reinvent the humble stethoscope to save lives

12 min read
A health worker in Bangladesh listens to sounds from a boy’s lungs with the help of the Johns Hopkins smart stethoscope
Photo: Dr. Eric D. McCollum

Tech for a Noisy World: Researchers simulated an extremely noisy environment in the lab (the sound meter shows levels of around 70 decibels). They compared the audio heard through a top-notch commercial stethoscope, in which the breathing sounds are mixed with ambient noise, to that heard through the Johns Hopkins smart stethoscope, which uses active acoustic filtering to isolate the breathing sounds.Video: Johns Hopkins University

You wake up one morning to discover that your child is ill: His forehead feels hot to the touch, and his rapid breathing has a wheezing sound. You live in Malawi, where your health care options are few. When the local clinic opens, you wait for your turn with the solitary clinic worker. She’s not a doctor, but she’s been trained to identify and handle routine problems.

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Video Friday: Humanoid Soccer

Your weekly selection of awesome robot videos

4 min read
Humans and human-size humanoid robots stand together on an indoor soccer field at the beginning of a game

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

CoRL 2022: 14–18 December 2022, AUCKLAND, NEW ZEALAND
ICRA 2023: 29 May–2 June 2023, LONDON

Enjoy today’s videos!

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Computing With Chemicals Makes Faster, Leaner AI

Battery-inspired artificial synapses are gaining ground

5 min read
Array of devices on a chip

This analog electrochemical memory (ECRAM) array provides a prototype for artificial synapses in AI training.

IBM research

How far away could an artificial brain be? Perhaps a very long way off still, but a working analogue to the essential element of the brain’s networks, the synapse, appears closer at hand now.

That’s because a device that draws inspiration from batteries now appears surprisingly well suited to run artificial neural networks. Called electrochemical RAM (ECRAM), it is giving traditional transistor-based AI an unexpected run for its money—and is quickly moving toward the head of the pack in the race to develop the perfect artificial synapse. Researchers recently reported a string of advances at this week’s IEEE International Electron Device Meeting (IEDM 2022) and elsewhere, including ECRAM devices that use less energy, hold memory longer, and take up less space.

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NYU Biomedical Engineering Speeds Research from Lab Bench to Bedside

Intensive clinical collaboration is fueling growth of NYU Tandon’s biomedical engineering program

5 min read

This optical tomography device that can be used to recognize and track breast cancer, without the negative effects of previous imaging technology. It uses near-infrared light to shine into breast tissue and measure light attenuation that is caused by the propagation through the affected tissue.

A.H. Hielscher, Clinical Biophotonics Laboratory

This is a sponsored article brought to you by NYU’s Tandon School of Engineering.

When Andreas H. Hielscher, the chair of the biomedical engineering (BME) department at NYU’s Tandon School of Engineering, arrived at his new position, he saw raw potential. NYU Tandon had undergone a meteoric rise in its U.S. News & World Report graduate ranking in recent years, skyrocketing 47 spots since 2009. At the same time, the NYU Grossman School of Medicine had shot from the thirties to the #2 spot in the country for research. The two scientific powerhouses, sitting on opposite banks of the East River, offered Hielscher a unique opportunity: to work at the intersection of engineering and healthcare research, with the unmet clinical needs and clinician feedback from NYU’s world-renowned medical program directly informing new areas of development, exploration, and testing.

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