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explainable ai

2,123 papers

#explainable ai Review Open access Oct 2026

ARTIFICIAL INTELLIGENCE IN MEDICAL EDUCATION AND CLINICAL PRACTICE: A NARRATIVE REVIEW

AI delivers its greatest value when deployed as a collaborative instrument that augments rather than replaces clinical judgment, which depends on sustained investment in digital literacy, explainable systems, clinician involvement in design, and equitable institutional infrastructure.

A. Bociąg, Łukasz Ptach, Rafał Marciniak et al. · 0 citations
#explainable ai Oct 2026

Artificial intelligence driven framework for enhancing sustainability and resilience in communal cattle insurance in Lupane District Zimbabwe

Communal cattle farming in Sub-Saharan Africa continues to face destabilization from non-linear climate variability, yet insurance penetration remains negligible. In Lupane District, Zimbabwe, uptake is exceptionally low at approximately 0.01%, despite recurrent droughts that threaten household livelihoods. This study...

N. Nyakuchena, J. Musara, E. Zivenge · 0 citations
#explainable ai Book Open access Oct 2026

ECHO: Explainable Co-editing with Human-in-the-loop Operations for Presentation Slide Refinement

Authoring and refining presentation slides is time-consuming in academic and professional settings. Although generative AI lowers the barrier to creating initial drafts, its black-box, one-way workflow often limits fine-grained control. A formative study with 10 frequent presentation authors identified trial-and-error...

Yu Fu, Yong-Qi Kang, Yu-Jia Zhou et al. · 0 citations
#data science Open access Dec 2026

Teaching Data Cleaning in Machine Learning: A Misconception-Driven Pedagogical Framework for Explainable and Ethical Data Preprocessing

Data cleaning — the process of detecting and remedying missing, erroneous, and inconsistent records in raw datasets — is widely recognized as the most time-consuming and consequential stage of the machine learning preprocessing pipeline. Yet despite its operational centrality, how data cleaning should be taught to unde...

Feyzi Kaysi, Serdar Yilmaz, Canan Akay · 0 citations
#explainable ai Dataset Open access Oct 2026

METHODS AND MODELS FOR OPTIMIZING FINANCIAL AND ADMINISTRATIVE PROCESSES THROUGH ARTIFICIAL INTELLIGENCE

The rapid development of artificial intelligence (AI), machine learning (ML), natural language processing (NLP), predictive analytics, and intelligent automation is transforming the organization of financial and administrative processes. Financial administration traditionally depends on large volumes of structured and...

MUHAMMADIEVA AZIZA SHARIFOVNA, Worldly Knowledge Publishing Centre · 0 citations
#explainable ai Open access Oct 2026

A proof of a conjecture of R. Ford: semi-meanders with two mountain ranges and Euler's totient function

We prove a conjecture of R. Ford stated in 2017 in the OEIS entry A000010 (Euler's totient function): for n > 1, the number of semi-meander solutions for n whose top arches contain exactly 2 mountain ranges and exactly 2 arches of length 1 equals phi(n). In Ford's setting, the points 1, ..., 2n lie on a line, the botto...

Roberto Blanco Gómez · 0 citations
#explainable ai Open access Oct 2026

Phonon–Photon–Spin Transduction: A First-Principles Pedagogical Derivation from Lattice Vibrations to Conditional Spin Response

This pedagogical technical note derives a connected model from a one-dimensional monoatomic lattice through acoustic phonons, strain, photoelastic refractive-index modulation, Stokes and anti-Stokes optical sidebands, and a conditional spin-population response. It explains why a realistic optical-to-spin step requires...

Chaman Prakash Kanth · 0 citations
#explainable ai Open access Oct 2026

Machine learning and Voronoi-based decision boundaries for Bacterial vaginosis to determine population- specific microbial interactions.

In this study we utilize machine learning techniques to create predictive models and determine key bacterial interactions for the diagnosis of Bacterial vaginosis. Bacterial vaginosis (BV) is a common vaginal syndrome affecting reproductive-age women globally. It is associated with various adverse obstetric and gynecol...

Cameron Celeste, C. C. Sokolik, W. Gachunga et al. · 0 citations
#explainable ai Open access Oct 2026

Potential Dangers of AI in Teaching: An Ecological Analysis of Teacher Agency

Drawing on Priestley, Biesta, and Robinson’s ecological approach to teacher agency, and on Biesta and Tedder’s account of agency as an ecological achievement, this paper defines teacher agency not as a personal trait but as something achieved through the interaction of past experience, future orientation, present judge...

Wang Wei · 0 citations

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Microsoft Research Blog Oct 7, 2026

Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses

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.

Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

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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