PRESS-NEWS.org - Press Release Distribution
PRESS RELEASES DISTRIBUTION

New machine learning technique 30% better at predicting cancer cure rates

UTA study is first to integrate two types of modeling techniques to predict cancer recurrences

New machine learning technique 30% better at predicting cancer cure rates
2023-11-20
(Press-News.org) With the rapid development in computing power over the past few decades, machine-learning (ML) techniques have become popular in medical settings as a way to predict survival rates and life expectancies among patients diagnosed with diseases such as cancer, heart disease, stroke, and, more recently, COVID-19. Such statistical modeling helps patients and caregivers balance treatment that offers the highest chance of a cure while minimizing the consequences of potential side effects.

A professor and his doctoral student at The University of Texas at Arlington have published a new model of predicting survival from cancer that they say is 30% more effective than previous models in predicting who will be cured of disease. This model can help patients avoid treatments they don’t need while allowing treatment teams to focus instead on others who need additional interventions.

“Previous studies modeling the probability of a cure, also called the cure rate, used a generalized linear model with a known parametric link function such as the logistic link function. However, this type of research doesn’t capture non-linear or complex relationships between the cure probability and important covariates, such as the age of the patient or the age of a bone marrow donor,” said principal investigator Suvra Pal, associate professor of statistics in the Department of Mathematics. “Our research takes the previously tested promotion time cure model (PCM) and combines it with a supervised type of ML algorithm called a support vector machine (SVM) that is used to capture non-linear relationships between covariates and cure probability.”

Supported by a grant from the National Institute of General Medical Sciences, the new SVM-integrated PCM model (PCM-SVM) is developed in a way that builds upon a simple interpretation of covariables to predict which patients will be uncured at the end of their initial treatment and need additional medical interventions.

To test the technique, Pal and his student Wisdom Aselisewine took real survival data for patients with leukemia, a type of blood cancer that is often treated with a bone marrow transplant. The researchers chose leukemia because it is caused by the rapid production of abnormal cancerous, white blood cells. Since this does not happen in healthy people, they were able to clearly see which patients in the historic data set were cured by treatments and which were not.

Both statistical models were tested and the newer PCM-SVM technique was found to be 30% more effective at predicting who would be cured by the treatments compared to the previous technique.

“These findings clearly demonstrate the superiority of the proposed model,” Pal said. “With our improved predictive accuracy of cure, patients with significantly high cure rates can be protected from the additional risks of high-intensity treatments. Similarly, patients with low cure rates can be recommended timely treatment so that the disease does not progress to an advanced stage for which therapeutic options are limited. The proposed model will play an important role in defining the optimal treatment strategy.”

END

[Attachments] See images for this press release:
New machine learning technique 30% better at predicting cancer cure rates

ELSE PRESS RELEASES FROM THIS DATE:

Potential therapeutic target found to combat tuberculosis, a disrupted NAD(H) homeostasis

Potential therapeutic target found to combat tuberculosis, a disrupted NAD(H) homeostasis
2023-11-20
BIRMINGHAM, Ala. – It has been uncertain how Mycobacterium tuberculosis deflects the immune response in humans, though evidence has pointed to host immunometabolism — the intrinsic link between metabolism in immune cells and their immune function. The pathogen M. tuberculosis is known to disrupt a metabolic pathway called glycolysis in infected myeloid cells, which include macrophages, through an unclear mechanism. A more accurate understanding of this pathogenic mechanism could provide a target against the bacterium that caused 1.6 million deaths in 2021, along with 10 million new cases of tuberculosis every year. Now a study published ...

Global Neuroanatomy Network (GNN): Creating a new resource for neuro educators

2023-11-20
In a leap forward for neuroanatomy education, the Global Neuroanatomy Network (GNN) is about to launch, creating a new, accessible, peer-reviewed collection of resources for instructors around the world. Developed as a response to the challenges faced in transitioning neuroanatomy education to an online format during the pandemic, the GNN represents a collaborative effort by educators globally. The initiative began as a conversation on social media, recognizing the need for better resources and support for teaching neuroanatomy online. As educators ...

New research demonstrates more effective method for measuring impact of scientific publications

2023-11-20
Newly published research reexamines the evaluation of scientific findings, proposing a network-based methodology for contextualizing a publication’s impact. This new method, which is laid out in an article co-authored by Alex Gates, an assistant professor with the University of Virginia’s School of Data Science, will allow the scientific community to more fairly measure the impact of interdisciplinary scientific discoveries across different fields and time periods. The article was published ...

UCSB scientists will eliminate bottlenecks to breakthroughs with a newly acquired synthetic biology robotics system

2023-11-20
Researchers in UC Santa Barbara’s newly designated Biological Engineering (BioE) Department have received a significant boost from the U.S. Army, which awarded the university a $9.85 million grant to design and purchase state-of-the-art equipment that project leader Michelle O’Malley, a professor of chemical engineering and biological engineering, says “allows UCSB scientists to do things that we never thought were possible.” The funding, awarded through the Department of Defense’s Defense University Research ...

NASA’s Webb reveals new features in heart of Milky Way

NASA’s Webb reveals new features in heart of Milky Way
2023-11-20
The latest image from NASA’s James Webb Space Telescope shows a portion of the dense center of our galaxy in unprecedented detail, including never-before-seen features astronomers have yet to explain. The star-forming region, named Sagittarius C (Sgr C), is about 300 light-years from the Milky Way’s central supermassive black hole, Sagittarius A*. “There’s never been any infrared data on this region with the level of resolution and sensitivity we get with Webb, so we are seeing lots of features here for the first time,” said the observation team’s principal investigator Samuel Crowe, an undergraduate student at the University ...

UC Irvine-led study is first to find brain hemorrhage cause other than injured blood vessels

2023-11-20
Irvine, Calif., Nov. 20, 2023 — A first-of-its-kind study led by the University of California, Irvine has revealed a new culprit in the formation of brain hemorrhages that does not involve injury to the blood vessels, as previously believed. Researchers discovered that interactions between aged red blood cells and brain capillaries can lead to cerebral microbleeds, offering deeper insights into how they occur and identifying potential new therapeutic targets for treatment and prevention.   The ...

AI outperforms expert plastic surgeon in rhinoplasty consultations

AI outperforms expert plastic surgeon in rhinoplasty consultations
2023-11-20
In a new study, artificial intelligence in the form of ChatGPT outperformed an expert rhinoplasty surgeon in answering preoperative and postoperative patient questions related to nasal surgery. ChatGPT earned significantly higher ratings in accuracy, completeness, and overall quality, according to the study published in Facial Plastic Surgery & Aesthetic Medicine. Click here to read the article now. Kay Durairaj, MD, and Omer Baker, from Pasadena, California , Dario Bertossi, MD, from University of Verona, Steven Dayan, MD, from University of Illinois, Chicago, Kian Karimi, MD, from Los Angeles California, Roy Kim, MD, from San Francisco, California, Sam ...

People watched other people shake boxes for science. Here’s why

People watched other people shake boxes for science. Here’s why
2023-11-20
When researchers asked hundreds of people to watch other people shake boxes, it took just seconds for almost all of them to figure out what the shaking was for. The deceptively simple work by Johns Hopkins University perception researchers is the first to demonstrate that people can tell what others are trying to learn just by watching their actions. Published today in the journal Proceedings of the National Academy of Sciences, the study reveals a key yet neglected aspect of human cognition, and one with implications for artificial intelligence. “Just by looking ...

AI finds formula on how to predict monster waves

AI finds formula on how to predict monster waves
2023-11-20
Long considered myth, freakishly large rogue waves are very real and can split apart ships and even damage oil rigs. Using 700 years’ worth of wave data from more than a billion waves, scientists at the University of Copenhagen and University of Victoria have used artificial intelligence to find a formula for how to predict the occurrence of these maritime monsters. The new knowledge can make shipping safer. EMBARGOED CONTENT UNTIL MONDAY 20 NOVEMBER 2023 3 PM US EASTERN TIME Stories about monster waves, called rogue waves, have been the lore of sailors for centuries. But when a 26-metre-high rogue wave slammed into the Norwegian oil ...

Study reveals bias in AI tools when diagnosing women’s health issue

2023-11-20
Machine learning algorithms designed to diagnose a common infection that affects women showed a diagnostic bias among ethnic groups, University of Florida researchers found.  While artificial intelligence tools offer great potential for improving health care delivery, practitioners and scientists warn of their risk for perpetuating racial inequities. Published Friday in the Nature journal Digital Medicine, this is the first paper to evaluate fairness among these tools in connection to a women’s health issue. “Machine learning can be a great tool in medical diagnostics, but we found it can show bias toward different ethnic groups,” said Ruogu Fang, an associate ...

LAST 30 PRESS RELEASES:

Properties of new materials for microchips can now be measured well

Maltreated children are three times more likely to develop substance use disorders in adulthood

Two U professors selected as AAAS fellows

Dana-Farber Chief Scientific Officer, Kevin Haigis, PhD, elected as Fellow of the American Association for the Advancement of Science

Siblings with unique genetic change help scientists progress drug search for type 1 diabetes

Four MD Anderson researchers elected AAAS Fellows

Computational biology pioneer Katie Pollard elected as AAAS fellow

New “window-of-opportunity” clinical trials explore cutting-edge treatments for cancers of the liver, head and neck

Can bismuth prevent oil leaks – (and save Norwegians billions)?

Atmospheric isotopes reveal 4.5 billion years of volcanism on Jupiter’s moon Io

An ink for 3D-printing flexible devices without mechanical joints

Association for Chemoreception Sciences (AChemS) 46th Annual Meeting

How the Birmingham Drug Discovery Hub created an investment-ready ‘drug library’

Scientists uncover 95 regions of the genome linked to PTSD

AI tool predicts responses to cancer therapy using information from each cell of the tumor

CEOs’ human concern translates into higher stock price

Smoking-related deaths could be reduced if people attending lung cancer screening are offered stop-smoking support

Quick decisions in soccer enhanced by brain’s ability to suppress actions

Recycling CFRP waste is a challenge, but we've found a way to make it work

Advanced nuclear magnetic resonance technique developed to reveal precise structural and dynamical details in zeolites

Advancing performance assessment of a spectral beam splitting hybrid PV/T system with water-based SiO2 nanofluid

Researchers realize target protein stability analysis by time-resolved ultraviolet photodissociation mass spectrometry

Oxygen vacancies mediated ultrathin Bi4O5Br2 nanosheets as efficient piezocatalyst for synthesis of H2O2 from pure water

Warming and exogenous organic matter input affected temperature sensitivity and microbial carbon use efficiency of agricultural soil respiration on the Qinghai-Tibet Plateau

Eco-friendly glue designed by Cal Poly, Geisys Ventures team earns industry 'Innovation Award'

From dreams to reality: unveiling the ideal in situ construction method for lunar habitats and paving the way to Moon colonization

From theory to practice: Study demonstrates high CO2 storage efficiency in shale reservoirs using fracturing technology

What women want: Female experiences to manage pelvic pain

Study finds ChatGPT shows promise as medication management tool, could help improve geriatric health care

Heart failure, not stroke is the most common complication of atrial fibrillation

[Press-News.org] New machine learning technique 30% better at predicting cancer cure rates
UTA study is first to integrate two types of modeling techniques to predict cancer recurrences