explainable ai

The U.S. Occupational Radiation Dose Limit of 50 mSv per Year (10 C.F.R. § 20.1201(a)(i)): History, Physics, Regulations, and Practical Implications

This comprehensive review provides a detailed analysis of the 50 mSv annual occupational radiation dose limit as codified in the U.S. Nuclear Regulatory Commission (NRC) regulation 10 C.F.R. § 20.1201(a)(i). The paper traces the historical development of radiation protection standards from the early 20th century to the...

Artificial intelligence in non-small cell lung cancer: transforming diagnosis, treatment, and prognostic evaluation

Non-small cell lung cancer (NSCLC) is characterized by profound biological heterogeneity, frequently leading to late-stage diagnosis, recurrence, or metastasis. Conventional clinical pathways heavily depend on subjective visual interpretations, invasive tissue biopsies, and experience-based medical models that constrai...

Graph-Based Causal Inference for Explainable AI

Explainable AI (XAI) is a rapidly growing field focused on making AI models more transparent and understandable to humans. However, many existing XAI techniques primarily focus on post-hoc explanations, often without a deep understanding of the underlying causal relationships driving the model's decisions. This paper p...

The U.S. Occupational Radiation Dose Limit of 50 mSv per Year (10 C.F.R. § 20.1201(a)(i)): History, Physics, Regulations, and Practical Implications

This comprehensive review provides a detailed analysis of the 50 mSv annual occupational radiation dose limit as codified in the U.S. Nuclear Regulatory Commission (NRC) regulation 10 C.F.R. § 20.1201(a)(i). The paper traces the historical development of radiation protection standards from the early 20th century to the...

IMPROVING THE METHODOLOGY OF TEACHING ARABIC AS A FOREIGN LANGUAGE TO UNIVERSITY STUDENTS THROUGH GENERATIVE ARTIFICIAL INTELLIGENCE TECHNOLOGIES

The article examines the methodologically grounded integration of generative artificial intelligence technologies into the teaching of Arabic as a foreign language in higher education. The author proposes a model of teacher-mediated three-stage AI mediation, in which interaction with a language model comprises a teache...

Works for 9/6/2026 - Andrew Carnegie

Listen and ask questions on Gemini Noteboom: https://notebook.google.com/notebook/26cdfd36-008c-41cb-9bd4-e291f74f888c?authuser=1 Judge Justly: Agape, Telos, and Distributed Judgment in Future Artificial Agents develops a Catholic relational framework for the alignment of increasingly capable artificial agents. The pap...

A Comparative Study of Explainable (XAI) Deep and Ensemble Learning Models for a Web Application Firewall Using the FWAF Dataset

This study benchmarks machine learning (ML) and deep learning models for intrusion detection using the publicly available FWAF dataset, and emphasizes the value of balancing performance with interpretability, empowering Security Operations Centers (SOC) to validate automated decisions and foster trustworthy AI-driven w...

Assessing the Impact of Layer Selection on CAM-Based Explainability for YOLOv8: A Study on Hand-Sketched Digital Logic Circuits

Object detection has recently become a cornerstone task in computer vision. It allows the machine to identify and localise multiple objects in an image. With the development of deep learning, object detection systems have achieved remarkable performance in various domains such as autonomous driving, surveillance, healt...

What Is the Best AI Voice Recorder for Lectures?

Whether you're attending university classes, online courses, seminars, or professional training sessions, having a reliable way to capture every detail is essential. Many students are now looking for the best AI voice recorder, a lecture recorder and note taker, or simply a good voice recorder that can do more than rec...

Digital twins and explainable AI across the vaccine life cycle: from mRNA manufacturing to thermostability, cold-chain logistics, and immunisation services.

The evidence indicates that DTs are progressing from static simulations to operational twins for plasmid-to-mRNA production, supporting virtual commissioning, rapid scale-up and real-time optimisation, and XAI-enabled approaches improve stability prediction, and artificial intelligence of things (AIoT) architectures st...

Responsible AI-Assisted Assessment: A Human-in-the-Loop Protocol for Rubric-Aligned Scoring, Explainable Feedback, and Subgroup Fairness

Artificial intelligence in endometrial cancer: multimodal deep learning and future perspectives in precision gynecologic oncology — a structured narrative review

This structured narrative review summarizes AI applications in endometrial cancer, focusing on ultrasound imaging, radiomics, digital pathology, multimodal deep-learning, explainable AI, prognostic modeling, clinical translation, and future perspectives in personalized care.