Articles tagged with Artificial Intelligence
Researchers created an AI model that maps how genes work together inside human cells, helping to understand biology and disease. The Gene Set Foundation Model (GSFM) learns patterns in gene groupings and interactions across thousands of biological contexts.
Researchers developed NSYOLO, an AI framework that automatically segments and analyzes nanoparticles with high precision. The framework achieved a mean Average Precision (mAP@0.5) of 0.957, outperforming baseline models and traditional tools in complex imaging environments.
A recent study found that one-third of college students use generative AI to complete assignments, with 9% using it to cheat. The use of AI in higher education has sparked concerns about the validity of assessments and the credibility of university credentials. Researchers are urging assessment reform to address these issues.
Researchers from ECOG-ACRIN Cancer Research Group will present updated outcomes from the STAMP study on Merkel cell carcinoma, primary results from studies in glioblastoma and non-small cell lung cancer, and emerging approaches in precision oncology. AI-driven insights from the TAILORx breast cancer trial will also be showcased.
A new skin-like computing patch can analyze health data using artificial intelligence in mere milliseconds, directly on the body. It overcomes limitations of wearable devices by running AI computations within the body, improving response time for critical medical applications.
The University of Texas System has invested over $470 million in capital projects supporting UT San Antonio's growth as a top public research university. These investments span research, innovation, infrastructure, technology, and patient care, with a focus on expanding the university's research capabilities and technology infrastructure.
Researchers used top Generative AI models to grade hundreds of undergraduate essays, finding that AI only matched human-awarded degree classification around half the time. The AI systems were overly sensitive to linguistic features, giving out higher marks based on essay length and vocabulary range rather than academic quality.
Scientists at Tohoku University uncovered a hidden rule behind dual-atom catalysts, which follow a previously unknown 'dual-Sabatier optima' pattern. This discovery could accelerate the development of cheaper and more efficient fuel cells.
A new approach enables computers and machines to capture images at higher resolution and faster speed, making it impervious to reflective surfaces. The technology uses a virtual screen created by repurposing the surroundings of specular objects.
The University of Texas at San Antonio's three nominated researchers, Lyle Hood, Amina Qutub, and David L. Roberts, have made significant contributions to various fields, including medical devices, AI in healthcare, and mental health services.
A new AI system, Empirical Research Assistance (ERA), can automatically write scientific software programs that outperform human-written ones. ERA combines a large language model with search strategies to explore and refine thousands of pieces of code, reducing the time required for exploration from months to hours or days.
Researchers developed an AI framework, MouseMapper, to map disease-related changes in the entire mouse body. They found widespread inflammation and previously unrecognized damage to facial sensory nerves caused by obesity, which was also observed in human tissue.
A new AI-powered detection system developed by University of East London researchers combines language analysis with behavioural clues to identify genuine reviews. The hybrid fusion model achieved 93% accuracy on Amazon review data and 91% accuracy on Yelp reviews, outperforming traditional methods.
Shandong University researchers have developed MuSE-Promoter, a deep learning framework that integrates multiple complementary ways of looking at DNA sequences. The method consistently outperforms state-of-the-art tools in challenging cross-cell-line transfer and promoter-enhancer discrimination tasks.
A new report from Brookings Institution highlights the federal government's growing use of AI, but also notes significant disparities and bottlenecks to widespread adoption. Large agencies lead the way, while smaller agencies struggle with workforce capacity and trust issues.
Researchers are analyzing paired original and recurrent breast cancer tumors to identify biological factors driving recurrences years after treatment. The TAILORx and RxPONDER trials have provided a large dataset of clinically annotated tumor samples, enabling the study of late recurrence and potential prevention strategies.
A new model combines text mining and machine learning to extract service-specific aspects and customer actions from online reviews. The model effectively identifies core technical issues and user love for a platform, enabling targeted decisions for improvement. Researchers validated the model using 231,705 online reviews of Roblox.
A systematic review of AI models for meningioma segmentation reveals that better model architecture is the key driver of improved performance. The top models achieved high accuracy and efficiency, while future research focuses on making them more generalizable and efficient for real-world clinical settings.
Researchers have developed a framework called CHEEM that allows AI models to learn new tasks without losing performance on existing tasks. The framework improves adaptive intelligence by tailoring computational structure depending on task complexity.
A Harvard-led study developed BRIDGE, a simulation technology that reinterprets traditional non-disabled basketball footage into realistic wheelchair basketball video representations. The system significantly improved how natural player postures appeared and made tactical intentions easier to understand.
A recent study analyzing 18,000 articles on Grokipedia found that the AI-written encyclopedia systematically favors left-leaning news sources, while diverging in style and structure. The researchers argue that AI-generated systems like Grokipedia change how bias enters the system, often making it less visible.
Researchers create dataset for Meenzerisch dialect, but find large language models fail to understand and produce the dialect correctly. Accuracy rates as low as 4.24% and 0.56% are reported, highlighting need for linguistic diversity in digital applications.
Dr. Sandra Orsulic has received two federal awards totaling nearly $2 million to advance research aimed at improving outcomes for women with ovarian cancer. Her team will examine the body's inflammatory response after surgery and develop AI-powered tools to guide personalized treatment.
A new study from UC San Diego suggests that advanced large language models (LLMs) can exhibit human-like tone, humor, and fallibility in conversations, making it increasingly difficult for humans to distinguish between them and actual humans. This has major implications for how we think of AI, as the Turing test is no longer just about...
A new global consensus delivers guidelines for using tools like ChatGPT responsibly, protecting against fake references, data leaks, and machines masquerading as authors. The goal is to allow AI to assist with tasks like polishing English without compromising research integrity.
A new AI-powered cardiopulmonary resuscitation instructor has been developed to support bystanders during out-of-hospital cardiac arrests. The study suggests that this technology could be a scalable public health intervention to save lives.
TEGNet accelerates optimization in thermoelectric generator design by predicting performance with high accuracy and speed. The AI model enables designers to freely combine independent models for various materials, enabling complex structure exploration and high conversion efficiencies.
New research from North Carolina State University predicts data center power demand will increase by up to 57% by 2030, leading to higher electricity costs and CO2 emissions. The study finds that regional price increases will vary depending on where new data centers are built.
Researchers at Northwestern University and NIH emphasize the need to define plagiarism in AI-assisted research writing, as intellectual theft can occur without proper credit. The commentary recommends revising definitions of research misconduct to include GenAI tool misuse, promoting more responsible use.
A new study shows that an AI-powered CPR coaching agent can significantly improve survival rates by providing more accurate and comprehensive instructions. ChatCPR scored 100% on guideline-based CPR checklists and outperformed human dispatchers in guiding bystander resuscitation, with a 36-point gap in advanced steps.
A University of East London academic has published a book exploring how businesses can use AI, blockchain, and data analytics to become more adaptable and innovative. The publication argues that digital transformation is about people, strategy, and responsible leadership, not just technology.
Researchers identified 27 established patterns of corporate capture, including narrative capture and elusion of law, in news stories around global AI events. Big AI companies use tactics like deregulation and revolving doors to undermine regulation and enforcement.
Sociologist Mona Sloane argues AI's prediction paradigm reorganizes social relations and relationships. Her book 'Predicted: How AI Is Restructuring Social Life' advocates collective governance of AI as a form of infrastructure.
An AI technology successfully plans life-saving radiotherapy for cervical and prostate cancers, bridging the workforce gap and enabling more people to be treated. The ARCHERY trial found that the AI technology can achieve international best-practice radiotherapy planning in over 95% of cervical cancer cases.
The article discusses how AI is unlocking hidden potential in multimodal ophthalmic datasets, enabling high-precision screening and early detection of eye diseases. It highlights the integration of various imaging modalities and non-imaging data types to provide a comprehensive diagnostic framework.
Researchers at Chalmers University of Technology developed an AI method that adapts fast charging to the health of the battery, increasing its lifespan by almost 23%. The new strategy uses reinforcement learning and takes into account the battery's chemistry and state of health.