Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile
Articles by Karin Verspoor
Can AI do science?
Many of the most exciting discoveries in science involve highly specialised knowledge and making connections between far-flung facts. Scientists must combine deep analysis with broad reasoning strategies. As in many information-rich tasks, researchers are looking to artificial intelligence (AI) systems to speed up their work. AI tools may be able to support key steps such as generating ideas, reviewing existing work and analysing data.
‘AI scientists’ are improving, but what are the fundamental limits?
Karin Verspoor of RMIT University explores how AI is impacting research in STEM. A version of this article was originally published by The Conversation (CC BY-ND 4.0) Many of the most exciting discoveries in science involve highly specialised knowledge and making connections between far-flung facts. Scientists must combine deep analysis with broad reasoning strategies. As in many information-rich tasks, researchers are looking to artificial intelligence (AI) systems to speed up their work.
New 'AI scientists' are improving-but reveal their fundamental limits
; ; ; ; Continue reading More for You ; ; ; ; Continue reading More for You
New 'AI scientists' are improving—but reveal their fundamental limits
Credit: Unsplash/CC 0 Public Domain Many of the most exciting discoveries in science involve highly specialized knowledge and making connections between far-flung facts. Scientists must combine deep analysis with broad reasoning strategies. As in many information-rich tasks, researchers are looking to artificial intelligence (AI) systems to speed up their work. AI tools may be able to support key steps such as generating ideas, reviewing existing work and analyzing data.
New ‘AI scientists’ are improving – but reveal their fundamental limits
; ; ; Continue reading More for You
New ‘AI scientists’ are improving – but reveal their fundamental limits
Many of the most exciting discoveries in science involve highly specialised knowledge and making connections between far-flung facts. Scientists must combine deep analysis with broad reasoning strategies. As in many information-rich tasks, researchers are looking to artificial intelligence (AI) systems to speed up their work. AI tools may be able to support key steps such as generating ideas, reviewing existing work and analysing data.
New ‘AI scientists’ are improving – but reveal their fundamental limits
Many of the most exciting discoveries in science involve highly specialised knowledge and making connections between far-flung facts. Scientists must combine deep analysis with broad reasoning strategies. As in many information-rich tasks, researchers are looking to artificial intelligence (AI) systems to speed up their work. AI tools may be able to support key steps such as generating ideas, reviewing existing work and analysing data.
New ‘AI scientists’ are improving – but reveal their fundamental limits
and_machines / Unsplash Many of the most exciting discoveries in science involve highly specialised knowledge and making connections between far-flung facts. Scientists must combine deep analysis with broad reasoning strategies. As in many information-rich tasks, researchers are looking to artificial intelligence (AI) systems to speed up their work. AI tools may be able to support key steps such as generating ideas, reviewing existing work and analysing data.
AI-generated scientific papers will be inept and ineffective at innovating
Scientific discovery is one of the most sophisticated human activities. First, scientists must understand the existing knowledge and identify a significant gap. Next, they must formulate a research question and design and conduct an experiment in pursuit of an answer. Then, they must analyse and interpret the results of the experiment, which may raise yet another research question. Can a process this complex be automated?
Science or sausage factory? - Openforum
Scientific discovery is one of the most sophisticated human activities. First, scientists must understand the existing knowledge and identify a significant gap. Next, they must formulate a research question and design and conduct an experiment in pursuit of an answer. Then, they must analyse and interpret the results of the experiment, which may raise yet another research question. Can a process this complex be automated?
Newly Created 'AI Scientist' Is About to Start Churning Out Research
By signing up for our newsletter, you agree to our Terms of Use and Privacy Policy
Newly Created 'AI Scientist' Is About to Start Churning Out Research
Scientific discovery is one of the most sophisticated human activities. First, scientists must understand the existing knowledge and identify a significant gap. Next, they must formulate a research question and design and conduct an experiment in pursuit of an answer. Then, they must analyse and interpret the results of the experiment, which may raise yet another research question. Can a process this complex be automated?
A new 'AI scientist' can write science papers without any human input-here's why that's a problem
Continue reading More for You
A new 'AI scientist' can write science papers without any human input. Here's why that's a problem
New Delhi, Aug. 21 -- Scientific discovery is one of the most sophisticated human activities. First, scientists must understand the existing knowledge and identify a significant gap. Next, they must formulate a research question and design and conduct an experiment in pursuit of an answer. Then, they must analyse and interpret the results of the experiment, which may raise yet another research question. Can a process this complex be automated?
A new ‘AI scientist’ can write science papers without any human input. Here’s why that’s a problem
By Karin Verspoor, Dean, School of Computing Technologies, RMIT University, RMIT University Scientific discovery is one of the most sophisticated human activities. First, scientists must understand the existing knowledge and identify a significant gap. Next, they must formulate a research question and design and conduct an experiment in pursuit of an answer. Then, they must analyse and interpret the results of the experiment, which may raise yet another research question.
A new ‘AI scientist’ can write science papers without any human input. Here’s why that’s a problem
Scientific discovery is one of the most sophisticated human activities. First, scientists must understand the existing knowledge and identify a significant gap. Next, they must formulate a research question and design and conduct an experiment in pursuit of an answer. Then, they must analyse and interpret the results of the experiment, which may raise yet another research question. Can a process this complex be automated?
A new ‘AI scientist’ can write science papers without any human input. Here’s why that’s a problem
1 hour ago Dubai’s future is bright and Elon Musk knows it. Dubai seamlessly fuses its futuristic cityscape with the timeless beauty of the desert and ocean, making it a destination like no other. With ultramodern architecture and innovative infrastructure, the place has become a jewel of the United Arab …
‘Fighting fire with fire’ - using LLMs to combat LLM hallucinations
NEWS AND VIEWS 19 June 2024 The number of errors produced by an LLM can be reduced by grouping its outputs into semantically similar clusters. Remarkably, this task can be performed by a second LLM, and the method’s efficacy can be evaluated by a third. Text-generation systems powered by large language models (LLMs) have been enthusiastically embraced by busy executives and programmers alike, because they provide easy access to extensive knowledge through a natural conversational interface.
Integration of polygenic and gut metagenomic risk prediction for common diseases - Nature Aging
|
Abstract Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer.
By Yang Liu Verified, Scott Ritchie, Karin Verspoor, Veikko Salomaa, Aki S Havulinna, Guillaume Meric
|
Nature
Verified
[2402.03732] Deep Outdated Fact Detection in Knowledge Graphs
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
AI is already being used in healthcare - but not all of it is ‘medical grade’
Artificial intelligence (AI) seems to be everywhere these days, and healthcare is no exception. There is no doubt that in terms of patient health, workflows and system efficiency, AI will benefit the health system. But there are legitimate concerns about the accuracy of such tools For more stories, visit the Tech and Trends homepage. Artificial intelligence (AI) seems to be everywhere these days, and healthcare is no exception.
AI is already being used in healthcare. But not all of it is 'medical grade' Original
Artificial intelligence (AI) seems to be everywhere these days, and healthcare is no exception. There are computer vision tools that can detect suspicious skin lesions as well as a specialist dermatologist can. Other tools can predict coronary artery disease from scans. There are also data-driven robots that guide minimally-invasive surgery. To precisely diagnose diseases and guide treatment choices, AI is used to analyse patients’ genomic and molecular data.
AI is already being used in healthcare. But not all of it is 'medical grade'
16 hours ago A recent survey conducted by GitHub in partnership with Wakefield Research sheds light on the impact of artificial intelligence (AI) on the developer experience. The survey, which involved 500 U.S.-based developers from companies with 1,000-plus employees, focused on key aspects of their careers, …
AI is already being used in healthcare. But not all of it is 'medical grade'
Artificial intelligence (AI) seems to be everywhere these days, and healthcare is no exception. There are computer vision tools that can detect suspicious skin lesions[1] as well as a specialist dermatologist can. Other tools can predict coronary artery disease from scans[2]. There are also data-driven robots[3] that guide minimally-invasive surgery. To precisely diagnose diseases[4] and guide treatment choices[5], AI is used to analyse patients’ genomic and molecular data.
We need to chat about artificial intelligence
With the arrival of large language models such as ChatGPT, AI is reshaping how we work and interact Long foretold and often dismissed, artificial intelligence (AI) is now reshaping how we work and interact as a society.1 For every claim that AI is overhyped and underperforming, only weeks or months seem to pass before a new breakthrough asks us to re-evaluate what is possible.
We need to chat about artificial intelligence
Long foretold and often dismissed, artificial intelligence (AI) is now reshaping how we work and interact as a society. 1 For every claim that AI is overhyped and underperforming, only weeks or months seem to pass before a new breakthrough asks us to re-evaluate what is possible. Most recent, it is the very public arrival of large language models (LLMs) such as the generative pre-trained transformers (GPTs) in ChatGPT.
Analysis of predictive performance and reliability of classifiers for quality assessment of medical evidence revealed important variation by medical area
A major obstacle in deployment of models for automated quality assessment is their reliability. To analyse their calibration and selective classification performance. We examine two systems for assessing the quality of medical evidence, EvidenceGRADEr and RobotReviewer, both developed from Cochrane Database of Systematic Reviews to measure strength of bodies of evidence and risk of bias of individual studies, respectively.
Highlights • Non-invasive prediction of future liver disease using gut metagenomic sequencing • Prediction performance of gut microbiome is similar to that of conventional risk factors • Improved prediction accuracies by combining microbial and conventional predictors • Machine learning modeling with a large population-based prospective cohort Summary The gut microbiome has shown promise as a predictive biomarker for various diseases.
Using AI to predict hospital costs in real time
In many health systems around the world, running a hospital is a knife-edge balancing act. On one side are the doctors and nurses providing urgent, even critical care to patients. Their job is to do all they can. What is needed is a way to generate accurate estimates of costs early in a patient’s care. Picture: Getty Images On the other side are the hospital administrators making sure there are enough resources – medicines, equipment, beds, staff – to cope.
Use of a Victorian statewide surveillance program to evaluate the burden of healthcare‐associated Staphylococcus aureus bacteraemia and Clostridioides difficile infection in patients with cancer
Original Article Jake C. Valentine Corresponding Author jake.valentine@petermac.org orcid.org/0000-0002-3076-9182 National Centre for Infections in Cancer, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Victoria, Australia Correspondence Jake C.
Use of cefovecin in dogs and cats attending first-opinion veterinary practices in Australia
Electronic pages Original research Use of cefovecin in dogs and cats attending first-opinion veterinary practices in Australia http://orcid.org/0000-0001-5780-7567Laura Hardefeldt1,2, Brian Hur1,2,3, Karin Verspoor3,4, Timothy Baldwin3, Kirsten E Bailey1,2, Ri Scarborough1,2, Suzanna Richards1,5, Helen Billman-Jacobe1,2, Glenn Francis Browning1,2 and James Gilkerson2 1 National Centre for Antimicrobial Stewardship, Carlton, Victoria, Australia 2 Asia Pacific Centre for Animal Health,...
What the media tells us about gender diversity at work
The current pandemic has drawn attention to the still strongly gender-segregated patterns of work in Australia and globally. This ranges – who are more likely to be in precarious, face-to-face service work – to male-dominated political leadership that boosts the economy via male-dominated industries like construction, rather than female-dominated health, social assistance or education sectors. Gender segregation across industries is a major contributor to the gender gap in financial security.
Victoria's coronavirus contact tracing is about to get faster. Let's make it the first step in a larger digital boost
Victoria’s health authorities are now looking overseas for a reprieve following the federal government’s criticism of the state’s coronavirus response. The state government has enlisted US cloud-based software company Salesforce to administer a data management system in the health department to accelerate contact-tracing efforts. The government also plans to roll out five new “suburban response units” throughout Melbourne, using local insights and connections to speed up contact tracing.
Classification performance of administrative coding data for detection of invasive fungal infection in paediatric cancer patients
Loading metrics Open Access Peer-reviewed Research Article Jake C. Valentine , Leon J. Worth, Karin M. Verspoor, Lisa Hall, Daniel K. Yeoh, Karin A. Thursky, Julia E. Clark, Gabrielle M. Haeusler Jake C. Valentine, Leon J. Worth, Karin M. Verspoor, Lisa Hall, Daniel K. Yeoh, Karin A. Thursky, Julia E. Clark, Gabrielle M.
Use of cefovecin in dogs and cats attending first-opinion veterinary practices in Australia
Use of cefovecin in dogs and cats attending first-opinion veterinary practices in Australia http://orcid.org/0000-0001-5780-7567Laura Hardefeldt1,2, Brian Hur1,2,3, Karin Verspoor3,4, Timothy Baldwin3, Kirsten E Bailey1,2, Ri Scarborough1,2, Suzanna Richards1,5, Helen Billman-Jacobe1,2, Glenn Francis Browning1,2 and James Gilkerson2 1National Centre for Antimicrobial Stewardship, Carlton, Victoria, Australia 2Asia Pacific Centre for Animal Health, University of Melbourne, Parkville, Victoria,...
Describing the antimicrobial usage patterns of companion animal veterinary practices; free text analysis of more than 4.4 million consultation records
Loading metrics Open Access Peer-reviewed Research Article Brian A. Hur , Laura Y. Hardefeldt, Karin M. Verspoor, Timothy Baldwin, James R. Gilkerson Brian A. Hur, Laura Y. Hardefeldt, Karin M. Verspoor, Timothy Baldwin, James R. Gilkerson Published: March 13, 2020 https://doi.org/10.1371/journal.pone.0230049 Figures Abstract Antimicrobial Resistance is a global crisis that veterinarians contribute to through their use of antimicrobials in animals.
C'mon girls, let's program a better tech industry
Twitter is the latest tech company to reveal figures showing women are still underrepresented in the information and communication technology (ICT) workforce. Men make up 70% of the overall staff and women just 30%, according to a blog post by Janet Van Huysse, the company’s vice president for diversity and inclusion. But within technical jobs at the social media giant only one in ten of employees are women, she also revealed. Lately everyone seems to be talking about attracting women to ICT.
Automated Detection of Records in Biological Sequence Databases that are Inconsistent with the Literature
AbstractWe investigate and analyse the data quality of nucleotide sequence databases with the objective of automatic detection of data anomalies and suspicious records. Specifically, we demonstrate that the published literature associated with each data record can be used to automatically evaluate its quality, by cross-checking the consistency of the key content of the database record with the referenced publications.
How to keep more girls in IT at schools if we're to close the gender gap
The world is increasingly embracing digital technology, and so too are our schools. But many girls are still missing out on developing IT and programming skills. IT classes in schools mostly focus on basic skills, such as how to use email or spreadsheets, or use tablets to access online quizzes and educational games. Programming and algorithm-based problem solving don’t form a part of the typical school day. They tend to get taught only in extra-curricular classes, such as coding clubs.
The real reason more women don't code
I menstruate, and I code. I share this perhaps shocking personal information in the interest of full disclosure, and in solidarity with a new satirical campaign from Girls Who Code. The campaign proposes a simple explanation for the current low numbers of women in tech: that our hormonal cycles interfere with our ability to code. Other explanations offered up in the campaign include that women can’t code because their boobs get in the way or their long eyelashes make it hard to see the screen.
Show More
loading
Actions
Is this you?
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.Get in touch with Karin
Contact Karin, search articles and posts on X, monitor coverage, and track replies from one place.
Learn more about Muck Rack