AIMC Topic: Risk
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Existential risk narratives about AI do not distract from its immediate harms.
Proceedings of the National Academy of Sciences of the United States of America
Apr 17, 2025
There is broad consensus that AI presents risks, but considerable disagreement about the nature of those risks. These differing viewpoints can be understood as distinct narratives, each offering a specific interpretation of AI's potential dangers. On...
Sensitivity of a deep-learning-based breast cancer risk prediction model.
Physics in medicine and biology
Apr 17, 2025
When it comes to the implementation of deep-learning based breast cancer risk (BCR) prediction models in clinical settings, it is important to be aware that these models could be sensitive to various factors, especially those arising from the acquisi...
Impact of pectoral muscle removal on deep-learning-based breast cancer risk prediction.
Physics in medicine and biology
Feb 18, 2025
State-of-the-art breast cancer risk (BCR) prediction models have been originally trained on mammograms with pectoral muscle (PM) included. This study investigated whether excluding PM during training/fine-tuning improves the model's BCR discriminatio...
Multi-instance learning for identifying high-risk subregions associated with synchronous distant metastasis in clear cell renal cell carcinoma.
Medical physics
Oct 1, 2024
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most common histological subtypes of renal tumors.
Automated linguistic analysis in youth at clinical high risk for psychosis.
Schizophrenia research
Sep 17, 2024
Identifying individuals at clinical high risk for psychosis (CHRP) is crucial for preventing psychosis and improving the prognosis for schizophrenia. Individuals at CHR-P may exhibit mild forms of formal thought disorder (FTD), making it possible to ...
Zero- and few-shot prompting of generative large language models provides weak assessment of risk of bias in clinical trials.
Research synthesis methods
Aug 23, 2024
Existing systems for automating the assessment of risk-of-bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of availabl...
Development of a machine learning-based risk model for postoperative complications of lung cancer surgery.
Surgery today
Jun 19, 2024
PURPOSE: To develop a comorbidity risk score specifically for lung resection surgeries.
Systematic review of machine learning models in predicting the risk of bleed/grade of esophageal varices in patients with liver cirrhosis: A comprehensive methodological analysis.
Journal of gastroenterology and hepatology
Jun 17, 2024
Esophageal varices (EV) in liver cirrhosis carry high mortality risks. Traditional endoscopy, which is costly and subjective, prompts a shift towards machine learning (ML). This review critically evaluates ML applications in predicting bleeding risks...
Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.
International journal of biometeorology
Mar 8, 2024
In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other hand, the amount of precipitation reported annually was slightly less than the previous year. Similarly, the minimum-mean-maximum temperatures recorded...
Artificial intelligence and illusions of understanding in scientific research.
Nature
Mar 6, 2024
Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of ...
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