With millions of patients under its belt, digital health startup K Health is looking to scale its artificial intelligence technology in hospitals, starting with new strategic investor Cedars-Sinai.
The problem with turning to the internet.
With a new $59 million investment, digital health startup K Health is looking to scale its AI technology in hospitals, starting with new strategic investor Cedars-Sinai.
Globally, atherosclerotic cardiovascular disease (ASCVD) is the primary cause of illness and death and is much more common in with type 2 diabetes mellitus (T2DM) patients than non-diabetic individuals. Nevertheless, for approximately ten years, the identification of distinct prognostic risk biomarkers remains challenging.
In a recent study posted to the preprint server Research Square while under review for publication in Cardiovascular Diabetology, researchers investigate the prognostic value of serum proprotein convertase subtilisin/kexin type 9 (PCSK9) levels in T2DM patients to predict all-cause mortality and major adverse cardiovascular events (MACE).
While we are used to the idea of teeth only growing twice, a new drug could make it possible to grow a third set.
Scientists are making significant strides in the development of a groundbreaking drug that could potentially enable the regrowth of teeth.
Clinical trials are scheduled to commence in July next year. They hope it will be available for dentists to use by 2030.
A recent paper published in Nature Aging by researchers from Integrated Biosciences, a biotechnology company combining synthetic biology and machine learning.
Machine learning is a subset of artificial intelligence (AI) that deals with the development of algorithms and statistical models that enable computers to learn from data and make predictions or decisions without being explicitly programmed to do so. Machine learning is used to identify patterns in data, classify data into different categories, or make predictions about future events. It can be categorized into three main types of learning: supervised, unsupervised and reinforcement learning.
Ark Invest, which is led by CEO Cathie Wood, has been pouring money into semiconductor stocks lately and has made another notable purchase. According to portfolio updates published by the firm yesterday, Wood’s company has increased its investment in Quantum-Si (QSI-6.20%) — a small-cap biotech with a specialized, chip-based platform for protein sequencing.
Ark Invest regularly publishes information about stocks that have been bought and sold for its exchange-traded funds (ETFs), and a recent update showed it purchased more than 1.4 million shares of Quantum-Si stock for its Ark Genomic Revolution ETF (ARKG-1.84%) on Thursday. The purchase would have been valued at roughly $3.7 million based on the stock’s price at market close yesterday, and is the largest investment that Ark has made in the healthcare-tech upstart’s stock so far.
So the question is: Why is Wood excited about this little-known life sciences player?
Scientists have achieved a major breakthrough in combating ageing and age-related diseases. The study by the researchers from Harvard Medical School and Massachusetts Institute of Technology was published in the journal Aging-US.
Humanity’s attempt to prevent ageing: What is the breakthrough?
The researchers have introduced a chemical method through a ‘single pill’ to reprogram body cells, following which the cells effectively return to a younger state.
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2023 Clifford K et al. JAMA Network Open.
Corresponding Author: John C. Woodfield, PhD, Department of Surgical Sciences, Otago Medical School-Dunedin Campus, PO Box 913, Dunedin 9,054, New Zealand ([email protected]).
Author Contributions: Dr Woodfield had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
July 16 (Reuters) — Alzheimer’s disease experts are revamping the way doctors diagnose patients with the progressive brain disorder — the most common type of dementia — by devising a seven-point rating scale based on cognitive and biological changes in the patient.
The proposed guidelines, unveiled by experts on Sunday in a report issued at an Alzheimer’s Association conference in Amsterdam, embrace a numerical staging system assessing disease progression similar to the one used in cancer diagnoses. They also eliminate the use of terms like mild, moderate and severe.
The revamp — replacing guidelines issued in 2018 — was prompted by the increased availability of tests detecting key Alzheimer’s-related proteins such as beta amyloid in the blood and new treatments that require confirmation of disease pathology prior to use.