Diabetes mellitus is a serious chronic metabolic disease marked by continuous problems in the regulation of glucose and is linked to a wide range of cardiovascular, renal, neurological, ophthalmic and other complications. Because of the growing number of people with diabetes, the difficulty of providing individualized...
The idea behind personalized medicine is simple to explain but difficult to execute: prevention, diagnosis, prognosis and treatment should be based on the biological, clinical, environmental and behavioral specificities of the patient who is in front of the clinician, rather than the average patient of a trial populati...
Chittesh K. A.1, Thibiraj C.1, Jeyaprabha P.1*, Sambath Kumar R.1· European Journal Pharmaceuti...· 0 citations
Diabetes mellitus is a serious chronic metabolic disease marked by continuous problems in the regulation of glucose and is linked to a wide range of cardiovascular, renal, neurological, ophthalmic and other complications. Because of the growing number of people with diabetes, the difficulty of providing individualized...
The idea behind personalized medicine is simple to explain but difficult to execute: prevention, diagnosis, prognosis and treatment should be based on the biological, clinical, environmental and behavioral specificities of the patient who is in front of the clinician, rather than the average patient of a trial populati...
Chittesh K. A.1, Thibiraj C.1, Jeyaprabha P.1*, Sambath Kumar R.1· European Journal Pharmaceuti...· 0 citations
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Objective To leverage the chain-of-reasoning capability of DeepSeek-R1 (DS) to construct an AI patient capable of demonstrating the clinical reasoning process,and integrate it into PBL teaching for respiratory diseases,evaluating its effectiveness in improving students′ clinical reasoning skills,pathophysiological unde...
LIU Yuxi, XU Xiaofei, WANG Mingjie, XIANG Meng, YANG Dawei, YOU Linya, LIU Qiong· DOAJ (DOAJ: Directory of Ope...· 0 citations
Purpose: The rapid diffusion of artificial intelligence (AI) in organizational decision-making environments has intensified concerns about transparency, interpretability, and user trust. As complex machine learning models increasingly support managerial and policy decisions, the need for Explainable Artificial Intellig...
The proposed CA-Seq2Seq-LSTM-Attn framework is a promising decision-support tool for personalised dietary control in T2DM as it generates interpretable, nutritionally balanced and clinically matched meal recommendations.
Satish Singh Mekale, Maumita Chakraborty, Chiradeep Mukherjee· International Journal of Inf...· 0 citations
It is suggested that effective AI error recovery should maintain a professional baseline while adapting to the seriousness of the mistake, and value directness, clarity, accountability, and restraint over humor or highly human-like expression.
Anastasiia Satarenko· Adjunct Proceedings of the 1...· 0 citations
Findings from a structured Future Workshop involving 29 participants distributed across four thematic streams indicate that HCI challenges are not confined to interface design but pervade all six themes, and argue that forestry represents a rich and underexplored application domain for human-centered computing research...
M. Ferati, Fisnik Dalipi, Zenun Kastrati et al.· Adjunct Proceedings of the 1...· 0 citations
There's no denying that Artificial Intelligence (AI), Machine Learning (ML), and Big Data technologies are profoundly changing the face of software engineering and organizational leadership. As these technologies keep evolving, the design, deployment, and management of software systems are undergoing unprecedented chan...
Harsh Verma· International Journal of Eng...· 1 citation
This study delves into the notion of AI agentic architectures for autonomous data engineering pipelines and investigates the potential benefits of intelligent agents in enhancing automation, resilience, and decision-making processes in contemporary data ecosystems.
Harsh Verma· International journal of res...· 0 citations
The paper provides a comprehensive analytical tool to make sense of micro and macro evidence, unpacks scenarios when AI agents will drive inclusive productivity growth, and outlines a policy roadmap focused on complementary investments, incentives for task-redesign, and workforce transition support measures.
Harsh Verma· World Journal of Advanced Re...· 1 citation
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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