explainable ai

Beyond accuracy in crop classification: calibration, selective prediction, and robustness

Introduction: Near-perfect crop-label accuracy can conceal uncertainty, perturbation sensitivity, and weak explanations. This study evaluates these reliability dimensions without treating benchmark classification as an agronomic recommendation. Materials and methods: Ten classifiers were evaluated using five matched st...

Data Quality, Feature Engineering, and Model Reliability in Large-Scale AI Multi-Agentic Systems

Large-scale artificial intelligence (AI) systems increasingly operate not as a single monolithic model but as a population of interacting, specialized agents separate models or decision-making components responsible for functions such as pricing, fraud detection, ranking, routing, and customer support that share underl...

Scalable Real-Time Data Pipelines for AI and Machine Learning–Driven Enterprise Systems

The growth of enterprise data volumes across the 2000s and 2010s pushed traditional batch-oriented data processing infrastructures past their practical limits, motivating a sustained shift toward distributed, stream-based architectures capable of supporting real-time analytics and machine learning (ML). This article sy...

Evaluating domain generalization in agricultural deep learning through multi-seed LOSO validation and explainable AI

The combination of multi-seed LOSO validation, seed-level variability analysis, baseline benchmarking, and systematic XAI auditing constitutes a pre-deployment diagnostic framework for identifying generalization risks in agricultural computer-vision systems operating under spatial uncertainty.

Machine Learning in Hand Pathology Diagnosis: A Narrative Review of Current Insights

Machine learning (ML), a subset of artificial intelligence (AI), is revolutionizing health care. Given the intricate anatomy and functional complexity of the hand, AI applications in hand pathology are gaining prominence, particularly in the diagnosis of fractures, nerve injuries, and musculoskeletal disorders. This re...

Two further towers of congruences: the Genocchi numbers with a factor p, and the denominators of the Bernoulli numbers

Let G_m be the Genocchi numbers, G_m = 2(1 − 2^m) B_m, and p an odd prime. We prove that G_(2np^k) ≡ p · G_(2np^(k−1)) (mod p^(2k + 2 v_p(n))) for all n, k ≥ 1, and that this exponent is attained in most cases (552 of the 564 cases with p ≤ 59, k ≤ 3, 2np^k ≤ 800). The congruence is a direct consequence of the Kummer c...

Trust Rhythm in Human and AI Collaboration for Digital Marketing in Nonprofit and Service Organizations

This paper builds a conceptual model that explains how artificial intelligence changes the temporal structure of trust in a brand and defines the threshold beyond which automation erodes trust instead of supporting it. The study applies framework synthesis to peer-reviewed literature published from 2018 onward, supplem...

Agrifusion: An Agentic Multimodal Framework for Explainable and Multilingual Agricultural Decision Intelligence

Geological Reliability in Deep Learning Mineral Prospectivity Mapping: A Review

Artificial intelligence (AI)-based mineral prospectivity mapping (MPM) has rapidly advanced through the integration of deep learning, multisource geoscience data, and increasingly complex representation-learning approaches. However, the reliability of AI-derived prospectivity predictions remains a critical challenge be...

Enterprise AI Implementation: Why Teams Fail Without the Right Skills

Three months after deployment, Fortune 500 teams can't answer basic questions about their AI systems. David Ohnstad explains the fundamental mismatch: vendors design platforms for teams with skills that rarely exist in legacy enterprise environments. Full article: https://davidohnstad.net/enterprise-ai-implementation-t...

Model Business Intelligence Berbasis Explainable AI dan Analisis Ketidakpastian untuk Rekomendasi Strategi Penjualan UMKM

Penelitian ini mengembangkan model Business Intelligence yang mengintegrasikan Explainable AI dan analisis ketidakpastian untuk mendukung keputusan penjualan UMKM Coppo Awi. Data observasi mencakup 809 catatan produk-harian pada Januari–Juni 2025; sebanyak 739 observasi memenuhi kebutuhan fitur historis. Data dipisahka...

Statement of Intellectual Origin, Research Method, and AI Assistance

This document explains that Michael T. Dent, M.D.’s research process is driven by interdisciplinary conceptual synthesis across biology, chemistry, physics, medicine, and philosophy, with original ideas and hypotheses developed first and then tested against established theory, prior research, mathematics, and observati...