Lifeboat Foundation

As boosters say AI is primed to conquer entire sectors, from military to medicine, a significant portion of the tech world is surprisingly unconvinced by its utility, according to a new survey from software development business Retool.

In the survey of 1,500 people working in tech, Retool found that a startling 51.6 percent of people think AI is overrated, while 25.1 percent think it’s underrated, and another 23.4 percent think it’s fairly rated. The people surveyed include executives, software engineers, designers, and other positions in different industries.

Particularly striking was that workers in executive roles had a more favorable view of AI while people in the technical side “skewed a little more toward overrated” — perhaps not a surprise, since many business leaders have been crowing about the potential cost savings of AI and how it could generate more revenue.

A research team led by Professor Sei Kwang Hahn and Dr. Tae Yeon Kim from the Department of Materials Science and Engineering at Pohang University of Science and Technology (POSTECH) used gold nanowires to develop an integrated wearable sensor device that effectively measures and processes two bio-signals simultaneously. Their research findings were featured in Advanced Materials.

Wearable devices, available in various forms like attachments and patches, play a pivotal role in detecting physical, chemical, and electrophysiological signals for disease diagnosis and management. Recent strides in research focus on devising wearables capable of measuring multiple bio-signals concurrently.

However, a major challenge has been the disparate materials needed for each signal measurement, leading to interface damage, complex fabrication, and reduced device stability. Additionally, these varied signal analyses require further signal processing systems and algorithms.

Easy navigation in a rugged fitness landscape.

In a recent study published in the journal Scientific Reports, researchers compare whether insulin-and non-insulin-based insulin resistance (IR) markers could predict the risk of non-alcoholic fatty liver disease (NAFLD) in obese and non-obese individuals with no history of diabetes or hepatitis.

Study: Markers of insulin resistance associated with non-alcoholic fatty liver disease in non-diabetic population. Image Credit: Jo Panuwat D / Shutterstock.com.

About 10–15% of pregnancies fail after conception has been recognized, amounting to 23 million losses a year. Chromosomal anomalies underlie many embryonic and fetal losses, but their exact frequency and localization to the embryo or placenta are still unclear. A new study published in Nature Medicine reports on a chromosomal analysis of over 1,700 spontaneous early miscarriages.

The most common period of pregnancy loss is before the ninth week, though many may occur earlier and pass unrecognized. While about 11% of women have at least one miscarriage, the proportion goes down with two or three, at 2% and 0.7. respectively.

Implants and tiny machines could eventually be working inside our bodies to help treat disease or monitor activity, but letting them communicate is tricky. Now scientists at EPFL have developed a system whereby devices can communicate by releasing molecules into a patient’s bloodstream.

Biomedical implants play a key role in healthcare, monitoring activity in organs like the heart or brain, while recent research is investigating how nanoscale robots might one day swim or crawl through the body to fight disease. But these systems have a communication issue.

Running wires through the body is not only impractical, it’s an infection risk. And wireless technologies like radio, light and Bluetooth don’t travel through human tissue very efficiently, drastically limiting their range.

CU Cancer Center member, Michelle Springer, MS, CGC, presents “Genetic Testing for Family Members” at the Hereditary Cancer Conference.

Keynote lecture at Neuroinformatics 2016 in Reading, United Kingdom.
TRACK I — NORMAL DEVELOPMENT / COGNITION
Talk title: Typical and atypical development of large-scale brain networks.
Speaker: Vinod Menon, Stanford School of Medicine, USA

About INCF
The International Neuroinformatics Coordinating Facility (INCF) is an international non-profit organization devoted to advancing the field of neuroinformatics and global collaborative brain research. Learn more about INCF: www.incf.org

Nervous systems are complex networks, comprised of billions of neurons connected by trillions of synapses. These connections are subject to specific wiring rules that are thought to result from competitive selection pressures to minimise wiring costs and promote complex, adaptive function. While most connections in the brain are short-range, a smaller subset of metabolically costly projections extend over long distances to connect disparate anatomical areas. These long-range connections support integrated brain function and are concentrated between the most highly connected network elements; the hubs of the brain. Hub connectivity thus plays a vital role in determining how a given nervous system negotiates the trade-off between cost and value, and natural.
selection may favour connections that provide high functional benefit for low cost.

Consistent with this view, Professor Alex Fornito will present evidence.
that hub connectivity is under strong genetic control. He will show that the strength of connectivity between hubs in the human brain is more heritable than connectivity between other nodes, and that the genetic variants influencing hub connectivity overlaps with those implicated in mental illness and intelligence. He will also discuss the progress and challenges of developing generative models that evaluate the role of different cost-value trade-offs in driving complex brain topology.

Continue reading “Brain network hubs: maps, molecules, and models” »