A considerable number of papers have been published on the ethics of artificial intelligence for the purposes of violence risk assessment. In this issue of The Journal, Hogan and colleagues argue that artificial intelligence introduces novel concerns for violence risk assessment that require consideration. While the concerns that have been raised are entirely valid and require consideration, we argue that artificial intelligence does not herald a more serious or unique challenge in these areas relative to other forms of violence risk assessment.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.29158/JAAPL.210066-21 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Predictive modeling of diazinon residual concentration in soils contaminated with potentially toxic elements: a comparative study of machine learning approaches.
Biodegradation
December 2024
Department of Civil engineering, Islamic Azad university, Mashhad Branch, Iran.
The widespread use of pesticides, including diazinon, poses an increased risk of environmental pollution and detrimental effects on biodiversity, food security, and water resources. In this study, we investigated the impact of Potentially Toxic Elements (PTE) including Zn, Cd, V, and Mn on the degradation of diazinon in three different soils. We investigated the capability and performance of four machine learning models to predict residual pesticide concentration, including adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), radial basis function (RBF), and multi-layer perceptron (MLP).
View Article and Find Full Text PDFA novel generative multi-task representation learning approach for predicting postoperative complications in cardiac surgery patients.
J Am Med Inform Assoc
December 2024
AI for Health Institute, Washington University in St Louis, St Louis, MO 63130, United States.
Objective: Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identify and predict patient risks for postoperative complications. We developed and validated the effectiveness of predicting postoperative complications using a novel surgical Variational Autoencoder (surgVAE) that uncovers intrinsic patterns via cross-task and cross-cohort presentation learning.
View Article and Find Full Text PDF25th National and 11th International Annual Congress on Research and Technology of Iranian Medical Sciences Students, Urmia, Iran, 5-7 September, 2024.
Iran Biomed J
December 2024
Student Research Committee , Department of Nursing, Khalkhal University of Medical Sciences, Khalkhal, Iran.
Metabolic Engineering of Corynebacterium glutamicum for High-Level Production of 1,5-Pentanediol, a C5 Diol Platform Chemical.
Adv Sci (Weinh)
December 2024
Department of Chemical Engineering and Materials Science, Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, 03760, Republic of Korea.
The biobased production of chemicals is essential for advancing a sustainable chemical industry. 1,5-Pentanediol (1,5-PDO), a five-carbon diol with considerable industrial relevance, has shown limited microbial production efficiency until now. This study presents the development and optimization of a microbial system to produce 1,5-PDO from glucose in Corynebacterium glutamicum via the l-lysine-derived pathway.
View Article and Find Full Text PDFRevealing the heterogeneity of treatment resistance in less-defined subtype diffuse large B cell lymphoma patients by integrating programmed cell death patterns and liquid biopsy.
Clin Transl Med
January 2025
Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China.
Precision medicine in less-defined subtype diffuse large B-cell lymphoma (DLBCL) remains a challenge due to the heterogeneous nature of the disease. Programmed cell death (PCD) pathways are crucial in the advancement of lymphoma and serve as significant prognostic markers for individuals afflicted with lymphoid cancers. To identify robust prognostic biomarkers that can guide personalized management for less-defined subtype DLBCL patients, we integrated multi-omics data derived from 339 standard R-CHOP-treated patients diagnosed with less-defined subtype DLBCL from three independent cohorts.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!