SolvedByAI

Queue

628 cases were harvested and are backed by a real paper, but they fail the test the index publishes on. Each one is listed here with the reason, so the exclusion can be checked rather than trusted.

All 628 assisted 358 not a result 183 unsupported 87
Paper Year Cited Why it is held
Land Use and Land Cover Classification Meets Deep Learning: A Review Sensors 2023 123 not a result This is a systematic survey/review of deep-learning-based LULC classification methods, which presents no primary result of its own. “In this paper, we present a systematic review of deep-learning-based LULC classification”
Deep learning for accelerated and robust MRI reconstruction Magnetic Resonance Materials in Physics Biology and Medicine 2024 119 not a result The abstract explicitly states this is a review paper surveying existing DL approaches for MRI reconstruction, with no primary result produced. “This review paper provides a comprehensive overview of recent advances in DL for MRI reconstruction”
Quantitative interpretation explains machine learning models for chemical re... Nature Communications 2021 114 not a result The paper's contributions are an interpretability framework, bias diagnostics of an existing model, and a new benchmark dataset, tools and a benchmark that enable future work rather than an AI-produced primary result, with the Molecular Transformer being the object of study rather than the agent that solved anything. “We present a new debiased dataset that provides a more realistic assessment of model performance, which we propose as the new standard benchmark for c...”
State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic... JMIR Medical Informatics 2022 106 not a result This is a systematic review/survey of existing deep learning methods on ECG data, which presents no primary result of its own. “This study aimed to provide a systematic review of DL methods applied to ECG data for various clinical applications.”
Drug-drug interactions prediction based on deep learning and knowledge graph... iScience 2024 102 not a result This is a survey/review that summarizes and compares existing DDI prediction methods rather than producing a new result itself. “In this research, we aim to systematically review DDI prediction researches applying deep learning and graph knowledge.”
Artificial Intelligence Scribe and Large Language Model Technology in Health... Plastic & Reconstructive Surgery Global Open 2025 82 not a result This is a review/commentary summarizing advantages, limitations, and recommendations for AI scribe technology, with no primary result produced by an AI system. “Medical AI developers should use robust regulatory oversights, adhere to ethical guidelines, correct bias in algorithms, and improve detection and cor...”
DockStream: a docking wrapper to enhance de novo molecular design Journal of Cheminformatics 2021 76 not a result The paper's contribution is a software wrapper integrating existing docking backends into a generative design platform, i.e., a toolkit that enables work rather than a primary scientific result produced by an AI system. “DockStream is a flexible, stand-alone molecular docking wrapper that provides access to a collection of ligand embedders and docking backends.”
Machine learning in biohydrogen production: a review Biofuel Research Journal 2023 76 not a result This is a review paper surveying machine learning applications in biohydrogen production, with no primary result produced by an AI system. “This review critically reviews the role of machine learning in categorizing and predicting data related to biohydrogen production.”
Artificial intelligence for optimizing recruitment and retention in clinical... Journal of the American Medical Informatics Association 2024 76 not a result This is a scoping review that maps and summarizes existing literature on AI for clinical trial recruitment, producing no primary result of its own. “The objective of our research is to conduct a comprehensive review that aims to systematically map, describe, and summarize the current utilization of...”
A review of the applications of multi-agent reinforcement learning in smart... Frontiers in Robotics and AI 2022 76 not a result This is a literature review that surveys and maps existing MARL applications to smart factory attributes rather than producing a new AI-driven result. “In this research, we will review the literature on the applications of MARL to tasks within a smart factory and then demonstrate a mapping connecting...”
Deep learning for inferring transcription factor binding sites Current Opinion in Systems Biology 2020 70 not a result This is a review/survey paper that highlights recent advances and discusses future directions rather than presenting a primary research result. “Here we highlight timely advances in deep learning for genomics... We describe recent applications, model architectures, and advances in local and glo...”
Use of artificial intelligence for cancer clinical trial enrollment: a syste... JNCI Journal of the National Cancer Institute 2023 64 not a result This is a systematic review and meta-analysis synthesizing prior studies of AI trial-enrollment tools rather than an AI system producing a new primary result itself. “Articles were included if they reported on AI actively being used in the clinical trial enrolment process.”
Deep learning-based image segmentation for defect detection in additive manu... The International Journal of Advanced Manufacturing Technology 2024 53 not a result This is a survey/overview paper reviewing existing deep learning methods for AM defect detection, with no primary result produced by an AI system. “This paper presents an overview of computer vision-assisted patch-wise defect localization and pixel-wise segmentation methods reported for AM process...”
Deep learning analysis of resting electrocardiograms for the detection of my... European Heart Journal - Digital Health 2021 52 not a result This is a systematic review synthesizing 12 previously published studies rather than producing a new primary result, so it fails regardless of the AI content of the reviewed papers. “The aim of this review was to assess the evidence for deep learning (DL) analysis of resting electrocardiograms (ECGs) to predict structural cardiac p...”
NEURD offers automated proofreading and feature extraction for connectomics Nature 2025 40 not a result The paper's contribution is a software package/toolkit whose stated purpose is to enable and facilitate downstream analyses by researchers, not to report a primary result the AI itself produced. “These features enable many downstream analyses of neural morphology and connectivity, making these massive and complex datasets more accessible to neu...”
A Systematic Review and Meta-Analysis of Applying Deep Learning in the Predi... Translational Vision Science & Technology 2023 36 not a result This is a systematic review and meta-analysis synthesizing prior studies of deep learning models; the paper's contribution is the literature synthesis itself, not any AI system producing a new result. “The purpose of this study was to perform a systematic review and meta-analysis to synthesize evidence from studies using deep learning (DL) to predict...”
Machine Learning-Driven Enzyme Mining: Opportunities, Challenges, and Future... ACS Catalysis 2025 35 not a result This is a review/survey summarizing existing ML models and case studies in enzyme mining, with no primary result produced by an AI system. “This review provides a systematic overview of state-of-the-art machine learning models and highlights representative case studies that demonstrate the...”
Best practices for developing microbiome-based disease diagnostic classifier... Gut Microbes 2025 33 not a result This is a benchmarking/best-practices study that re-runs and compares 156 existing tool-parameter-algorithm combinations to derive recommendations and a guideline for building classifiers, rather than an AI system producing a primary solved result. “can provide a comprehensive guideline for constructing diagnostic models for a range of diseases”
Multivariate Analysis and Machine Learning in Cerebral Palsy Research Frontiers in Neurology 2017 32 not a result This is a survey/review paper summarizing prior multivariate and machine learning studies in cerebral palsy research, with no primary result produced by any AI system. “This paper aims to identify such multivariate studies and provide an overview of this relatively young field.”
Data-driven strategies for the computational design of enzyme thermal stabil... Acta Biochimica et Biophysica Sinica 2023 28 not a result This is a review/perspective summarizing datasets, methods, and future directions rather than reporting a primary result produced by an AI system. “In this review, we propose a data-driven architecture for enzyme thermostability engineering and summarize some widely adopted datasets, as well as ma...”
Identifying Regulatory Elements via Deep Learning Annual Review of Biomedical Data Science 2020 23 not a result This is a survey/review of deep learning methods in regulatory genomics, with no primary result produced by an AI system. “In this review, we survey the successes of deep learning in the field of regulatory genomics.”
Performance of Machine Learning for Tissue Outcome Prediction in Acute Ische... Frontiers in Neurology 2022 23 not a result This is a systematic review and meta-analysis that synthesizes prior studies' ML performance rather than producing any new AI-driven result itself. “This study aimed to provide a systematic review and meta-analysis of the overall performance of current ML algorithms for final infarct prediction fro...”
Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning: A S... Frontiers in Public Health 2022 23 not a result This is a systematic literature review surveying existing arbovirus prediction models, with no primary result produced by any AI system. “In this study, we propose a systematic literature review to identify arboviruses prediction models, as well as models for their transmitter vector dyn...”
Limits of Prediction for Machine Learning in Drug Discovery Frontiers in Pharmacology 2022 21 not a result This is a benchmark-style evaluation that re-runs six standard ML algorithms on 243 existing datasets to characterize extrapolation error, with no primary discovery result produced or solved by the AI. “this study examined the capabilities of six machine learning algorithms to extrapolate from 243 datasets”
A Comprehensive Review of Machine-Learning Approaches for Crystal Structure/... Crystals 2025 12 not a result This is a survey/review paper summarizing ML methods for crystal structure and property prediction, with no primary result of its own. “This review provides a comprehensive overview of the evolution of CSP and CPP methodologies”
Challenges in Testing Large Language Model-Based Software: A Faceted Taxonom... ACM Transactions on Software Engineering and Methodology 2026 4 not a result The paper's contribution is a taxonomy of test-case design challenges and open problems, not a primary result that any AI system produced; the LLM-assisted framework analysis is merely illustrative support for the taxonomy. “This article presents a taxonomy for LLM test case design, informed by research literature and our experience.”
Medical image segmentation using deep learning: A survey IET Image Processing 2022 845 not a result This is a survey paper that reviews and classifies existing literature on deep learning for medical image segmentation, producing no primary result of its own. “we present a comprehensive thematic survey on medical image segmentation using deep learning techniques”
Machine learning paradigm for structural health monitoring Structural Health Monitoring 2020 372 not a result The abstract describes a perspective/review article that proposes a conceptual paradigm and surveys challenges rather than presenting an AI system that produced a primary result. “This article sheds light on principles for machine learning paradigm for structural health monitoring with some examples and reviews the existing chal...”
Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Dr... Journal of Chemical Information and Modeling 2018 345 not a result The paper's contribution is a proposed evaluation metric for generative models, not a scientific result produced by an AI system; it is a tool/framework enabling future work. “We propose an evaluation metric for generative models called Fréchet ChemNet distance (FCD).”
Machine Learning and Deep Learning Methods for Skin Lesion Classification an... Diagnostics 2021 270 not a result This is a systematic review synthesizing prior published studies rather than presenting a new AI-produced result. “This paper aims to review, synthesize and evaluate the quality of evidence for the diagnostic accuracy of computer-aided systems.”
Process monitoring and machine learning for defect detection in laser-based... Journal of Intelligent Manufacturing 2023 239 not a result This is a critical review/survey of ML approaches for defect detection in additive manufacturing, not a primary result produced by an AI system. “the application of various Machine Learning (ML) approaches and in-situ monitoring technologies for the purpose of defect detection are reviewed”
The emergence of large language models as tools in literature reviews: a lar... Journal of the American Medical Informatics Association 2025 145 not a result This is a systematic review/survey summarizing existing literature on LLM usage in review automation, which falls under reviews that only synthesize others' work, regardless of the AI assistance embedded in its own pipeline. “Our LLM-assisted systematic review revealed a significant number of research projects related to review automation using LLMs.”
Machine learning applied to retinal image processing for glaucoma detection:... BioMedical Engineering OnLine 2020 138 not a result This is a systematic review summarizing prior ML studies on glaucoma detection, with no primary result produced by an AI system. “This is a systematic review on the main algorithms using machine learning (ML) in retinal image processing for glaucoma diagnosis and detection.”
Deep-Learning-Based Image Reconstruction and Enhancement in Optical Microsco... Proceedings of the IEEE 2019 136 not a result The abstract explicitly states this is an overview/survey of recent deep learning work in computational microscopy, not a primary research result. “This article provides an overview of some of the recent work using deep neural networks to advance computational microscopy and sensing systems, also...”
Protein Function Prediction: From Traditional Classifier to Deep Learning PROTEOMICS 2019 132 not a result This is a commentary/review summarizing Zhang et al.'s DeepFunc work rather than presenting a primary result of its own. “In article number 1900019, Issue 12, Zhang et al. construct DeepFunc, a deep learning framework using derived feature information of protein sequence...”
Large language models for structured reporting in radiology: past, present,... European Radiology 2024 129 not a result This is a narrative review surveying existing literature on LLMs for structured reporting, with no primary result produced by an AI system. “this narrative review aims to provide an overview of LLMs for SR in radiology and beyond”
DeepBacs for multi-task bacterial image analysis using open-source deep lear... Communications Biology 2022 119 not a result The paper is a toolkit/guide with a training database that enables users to apply deep learning to bacterial imaging, rather than reporting a primary solved result. “DeepBacs guides users without expertise in machine learning methods to leverage state-of-the-art artificial neural networks to analyse bacterial micro...”
Evaluation of Surgical Skills during Robotic Surgery by Deep Learning-Based... Journal of Clinical Medicine 2020 107 not a result the paper is a study ("evaluation of…"): it measures or reviews work rather than producing a result for an AI to have solved
Benchmarking deep learning splice prediction tools using functional splice a... Human Mutation 2021 100 not a result This is a benchmarking study that re-runs and evaluates existing splice prediction tools against functional assay data rather than producing a new AI-driven result. “We benchmarked established and deep learning splice prediction tools on published gold standard sets of 71 NCSS and 81 DI variants”
Comparative validation of machine learning algorithms for surgical workflow... Medical Image Analysis 2023 100 not a result This is a benchmark/dataset paper whose contribution is the HeiChole dataset and comparative evaluation of 12 external teams' algorithms, not an AI system producing a primary result. “This novel HeiChole benchmark can be used for comparable evaluation and validation of future work.”