{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/medical-diagnosis/papers/7","list_of":"/task/medical-diagnosis","task":"Medical Diagnosis","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":7,"pages_in_order":8,"rows_per_page":100,"rows":[601,700],"of":714,"counts":{"archive_papers_tagged":714,"with_a_code_link":222,"where_syntology_ran_a_sample":43,"not_listed_spam_title":0,"listed":714,"listed_where_code_ran":43,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":36,"every_run_a_failure_of_syntologys_instrument":7,"listed_with_a_run_with_no_instrument_failure":36,"listed_every_run_a_failure_of_syntologys_instrument":7,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/medical-diagnosis","prev":"/task/medical-diagnosis/papers/6","next":"/task/medical-diagnosis/papers/8","papers":[{"url":null,"slug":"fusion-of-convolutional-neural-network-and","title":"Fusion of Convolutional Neural Network and Statistical Features for Texture classification","date":"2019-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"adapting-to-label-shift-with-bias-corrected","title":"Adapting to Label Shift with Bias-Corrected Calibration","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bias-resilient-neural-network-1","title":"Bias-Resilient Neural Network","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"verification-and-validation-of-computer","title":"Verification and Validation of Computer Models for Diagnosing Breast Cancer Based on Machine Learning for Medical Data Analysis","date":"2019-09-21","arxiv_id":"1910.02779","repositories_listed":0,"syntology":null},{"url":null,"slug":"value-of-information-in-probabilistic-logic","title":"Value of Information in Probabilistic Logic Programs","date":"2019-09-18","arxiv_id":"1909.08234","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-blood-cell-detection-and-counting","title":"Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices","date":"2019-09-11","arxiv_id":"1909.05393","repositories_listed":0,"syntology":null},{"url":null,"slug":"disease-labeling-via-machine-learning-is-not","title":"Disease Labeling via Machine Learning is NOT quite the same as Medical Diagnosis","date":"2019-09-08","arxiv_id":"1909.03470","repositories_listed":0,"syntology":null},{"url":null,"slug":"atypical-facial-landmark-localisation-with","title":"Atypical Facial Landmark Localisation with Stacked Hourglass Networks: A Study on 3D Facial Modelling for Medical Diagnosis","date":"2019-09-05","arxiv_id":"1909.02157","repositories_listed":0,"syntology":null},{"url":null,"slug":"gland-segmentation-in-histopathology-images-1","title":"Gland Segmentation in Histopathology Images Using Deep Networks and Handcrafted Features","date":"2019-08-31","arxiv_id":"1909.00270","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-in-healthcare-a-survey","title":"Reinforcement Learning in Healthcare: A Survey","date":"2019-08-22","arxiv_id":"1908.08796","repositories_listed":0,"syntology":null},{"url":null,"slug":"rgb-d-image-based-object-detection-from","title":"RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques","date":"2019-07-22","arxiv_id":"1907.09236","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-explanation-without-ground-truth","title":"Evaluating Explanation Without Ground Truth in Interpretable Machine Learning","date":"2019-07-16","arxiv_id":"1907.06831","repositories_listed":0,"syntology":null},{"url":null,"slug":"justifying-diagnosis-decisions-by-deep-neural","title":"Justifying Diagnosis Decisions by Deep Neural Networks","date":"2019-07-12","arxiv_id":"1907.05671","repositories_listed":0,"syntology":null},{"url":null,"slug":"strokesave-a-novel-high-performance-mobile","title":"StrokeSave: A Novel, High-Performance Mobile Application for Stroke Diagnosis using Deep Learning and Computer Vision","date":"2019-07-09","arxiv_id":"1907.05358","repositories_listed":0,"syntology":null},{"url":null,"slug":"dudonet-dual-domain-network-for-ct-metal-1","title":"DuDoNet: Dual Domain Network for CT Metal Artifact Reduction","date":"2019-06-29","arxiv_id":"1907.00273","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantifying-intrinsic-uncertainty-in","title":"Quantifying Intrinsic Uncertainty in Classification via Deep Dirichlet Mixture Networks","date":"2019-06-11","arxiv_id":"1906.04450","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-aware-deep-dual-networks-for-text","title":"Knowledge-Aware Deep Dual Networks for Text-Based Mortality Prediction","date":"2019-06-06","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-fuzzy-inference-system-for-the","title":"A Fuzzy Inference System for the Identification","date":"2019-05-02","arxiv_id":"1905.00991","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-temperature-scaling-post","title":"Unsupervised Temperature Scaling: An Unsupervised Post-Processing Calibration Method of Deep Networks","date":"2019-05-01","arxiv_id":"1905.00174","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-denoising-autoencoders-for-retinal","title":"Semantic denoising autoencoders for retinal optical coherence tomography","date":"2019-03-23","arxiv_id":"1903.09809","repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-modeling-for-novelty-detection","title":"Probabilistic Modeling for Novelty Detection with Applications to Fraud Identification","date":"2019-03-05","arxiv_id":"1903.01730","repositories_listed":0,"syntology":null},{"url":null,"slug":"effectiveness-of-lstms-in-predicting","title":"Effectiveness of LSTMs in Predicting Congestive Heart Failure Onset","date":"2019-02-07","arxiv_id":"1902.02443","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-diagnosis-with-a-novel-svm-codoa","title":"Medical Diagnosis with a Novel SVM-CoDOA Based Hybrid Approach","date":"2019-02-02","arxiv_id":"1902.00685","repositories_listed":0,"syntology":null},{"url":null,"slug":"discovery-of-important-subsequences-in","title":"Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour Algorithm","date":"2019-01-26","arxiv_id":"1901.09187","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-parkinsons-disease-using-latent","title":"Predicting Parkinson's Disease using Latent Information extracted from Deep Neural Networks","date":"2019-01-23","arxiv_id":"1901.07822","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-cost-device-prototype-for-automatic","title":"Low-Cost Device Prototype for Automatic Medical Diagnosis Using Deep Learning Methods","date":"2018-12-27","arxiv_id":"1901.00751","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-processing-on-iopa-radiographs-a","title":"Image Processing on IOPA Radiographs: A comprehensive case study on Apical Periodontitis","date":"2018-12-23","arxiv_id":"1812.09693","repositories_listed":0,"syntology":null},{"url":null,"slug":"wireless-network-intelligence-at-the-edge","title":"Wireless Network Intelligence at the Edge","date":"2018-12-07","arxiv_id":"1812.02858","repositories_listed":0,"syntology":null},{"url":null,"slug":"fuzzy-expert-system-for-prediction-of","title":"Fuzzy expert system for prediction of prostate cancer","date":"2018-12-01","arxiv_id":"1812.00236","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-classifications-of-coronary","title":"Machine Learning Classifications of Coronary Artery Disease","date":"2018-11-26","arxiv_id":"1812.02828","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-human-predictions-with-explanations-and","title":"On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection","date":"2018-11-19","arxiv_id":"1811.07901","repositories_listed":0,"syntology":null},{"url":null,"slug":"monotonic-classification-an-overview-on","title":"Monotonic classification: an overview on algorithms, performance measures and data sets","date":"2018-11-17","arxiv_id":"1811.07155","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-voice-controlled-e-commerce-web-application","title":"A Voice Controlled E-Commerce Web Application","date":"2018-11-16","arxiv_id":"1811.09688","repositories_listed":0,"syntology":null},{"url":null,"slug":"discovering-heterogeneous-subpopulations-for","title":"Discovering heterogeneous subpopulations for fine-grained analysis of opioid use and opioid use disorders","date":"2018-11-11","arxiv_id":"1811.04344","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-learning-of-probabilistic-models","title":"Effective Learning of Probabilistic Models for Clinical Predictions from Longitudinal Data","date":"2018-11-02","arxiv_id":"1811.00749","repositories_listed":0,"syntology":null},{"url":null,"slug":"identification-and-visualization-of-the","title":"Identification and Visualization of the Underlying Independent Causes of the Diagnostic of Diabetic Retinopathy made by a Deep Learning Classifier","date":"2018-09-23","arxiv_id":"1809.08567","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-examples-opportunities-and","title":"Adversarial Examples: Opportunities and Challenges","date":"2018-09-13","arxiv_id":"1809.04790","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-positive-and-unlabeled-data","title":"Learning from Positive and Unlabeled Data under the Selected At Random Assumption","date":"2018-08-27","arxiv_id":"1808.08755","repositories_listed":0,"syntology":null},{"url":null,"slug":"ct-image-super-resolution-using-3d","title":"CT-image Super Resolution Using 3D Convolutional Neural Network","date":"2018-06-24","arxiv_id":"1806.09074","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-decode-7t-like-mr-image","title":"Learning to Decode 7T-like MR Image Reconstruction from 3T MR Images","date":"2018-06-18","arxiv_id":"1806.06886","repositories_listed":0,"syntology":null},{"url":null,"slug":"gaussian-mixture-reduction-for-time","title":"Gaussian Mixture Reduction for Time-Constrained Approximate Inference in Hybrid Bayesian Networks","date":"2018-06-06","arxiv_id":"1806.02415","repositories_listed":0,"syntology":null},{"url":null,"slug":"pickleteam-at-semeval-2018-task-2-english-and","title":"PickleTeam! at SemEval-2018 Task 2: English and Spanish Emoji Prediction from Tweets","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improve-uncertainty-estimation-for-unknown","title":"Improve Uncertainty Estimation for Unknown Classes in Bayesian Neural Networks with Semi-Supervised /One Set Classification","date":"2018-05-04","arxiv_id":"1805.01955","repositories_listed":0,"syntology":null},{"url":null,"slug":"heteromed-heterogeneous-information-network","title":"HeteroMed: Heterogeneous Information Network for Medical Diagnosis","date":"2018-04-22","arxiv_id":"1804.08052","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-the-experts-from-expert-systems","title":"Learning from the experts: From expert systems to machine-learned diagnosis models","date":"2018-04-21","arxiv_id":"1804.08033","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-study-on-the-applications-of-1","title":"A Comprehensive Study on the Applications of Machine Learning for the Medical Diagnosis and Prognosis of Asthma","date":"2018-04-07","arxiv_id":"1804.04612","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-medical-diagnosis-and","title":"Weakly Supervised Medical Diagnosis and Localization from Multiple Resolutions","date":"2018-03-21","arxiv_id":"1803.07703","repositories_listed":0,"syntology":null},{"url":null,"slug":"construction-of-neural-networks-for","title":"Construction of neural networks for realization of localized deep learning","date":"2018-03-09","arxiv_id":"1803.03503","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-model-for-medical-diagnosis-based-on","title":"A Model for Medical Diagnosis Based on Plantar Pressure","date":"2018-02-28","arxiv_id":"1802.10316","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-interpretable-classifier-for","title":"A Deep Learning Interpretable Classifier for Diabetic Retinopathy Disease Grading","date":"2017-12-21","arxiv_id":"1712.08107","repositories_listed":0,"syntology":null},{"url":null,"slug":"convolutional-neural-networks-for-medical-1","title":"Convolutional Neural Networks for Medical Diagnosis from Admission Notes","date":"2017-12-06","arxiv_id":"1712.02768","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-practical-verification-of-machine","title":"Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems","date":"2017-12-05","arxiv_id":"1712.01785","repositories_listed":0,"syntology":null},{"url":null,"slug":"gazegan-unpaired-adversarial-image-generation","title":"GazeGAN - Unpaired Adversarial Image Generation for Gaze Estimation","date":"2017-11-27","arxiv_id":"1711.09767","repositories_listed":0,"syntology":null},{"url":null,"slug":"wikipedia-for-smart-machines-and-double-deep","title":"Wikipedia for Smart Machines and Double Deep Machine Learning","date":"2017-11-17","arxiv_id":"1711.06517","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-diagnosis-from-laboratory-tests-by","title":"Medical Diagnosis From Laboratory Tests by Combining Generative and Discriminative Learning","date":"2017-11-12","arxiv_id":"1711.04329","repositories_listed":0,"syntology":null},{"url":null,"slug":"crafting-adversarial-examples-for-speech","title":"Crafting Adversarial Examples For Speech Paralinguistics Applications","date":"2017-11-09","arxiv_id":"1711.03280","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-ct-quality-ultrasound-imaging-using","title":"Towards CT-quality Ultrasound Imaging using Deep Learning","date":"2017-10-17","arxiv_id":"1710.06304","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-evaluation-of-rule-extraction","title":"An Empirical Evaluation of Rule Extraction from Recurrent Neural Networks","date":"2017-09-29","arxiv_id":"1709.10380","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-objective-contextual-multi-armed-bandit","title":"Multi-objective Contextual Multi-armed Bandit with a Dominant Objective","date":"2017-08-18","arxiv_id":"1708.05655","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-machine-learning-for","title":"Application of machine learning for hematological diagnosis","date":"2017-08-01","arxiv_id":"1708.00253","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-sequential-neural-networks-with","title":"Stochastic Sequential Neural Networks with Structured Inference","date":"2017-05-24","arxiv_id":"1705.08695","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-medical-diagnosis-method-based-on-z","title":"A New Medical Diagnosis Method Based on Z-Numbers","date":"2017-05-07","arxiv_id":"1705.02620","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-labeling-free-approach-to-supervising-deep","title":"A Labeling-Free Approach to Supervising Deep Neural Networks for Retinal Blood Vessel Segmentation","date":"2017-04-25","arxiv_id":"1704.07502","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-and-the-future-of-realism","title":"Machine Learning and the Future of Realism","date":"2017-04-15","arxiv_id":"1704.04688","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-ensembles-of-quantum-classifiers","title":"Quantum ensembles of quantum classifiers","date":"2017-04-07","arxiv_id":"1704.02146","repositories_listed":0,"syntology":null},{"url":null,"slug":"annotation-of-negation-in-the-iula-spanish","title":"Annotation of negation in the IULA Spanish Clinical Record Corpus","date":"2017-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-and-inference-in-knowledge-based","title":"Learning and inference in knowledge-based probabilistic model for medical diagnosis","date":"2017-03-28","arxiv_id":"1703.09368","repositories_listed":0,"syntology":null},{"url":null,"slug":"linear-classifier-design-under","title":"Linear classifier design under heteroscedasticity in Linear Discriminant Analysis","date":"2017-03-24","arxiv_id":"1703.08434","repositories_listed":0,"syntology":null},{"url":null,"slug":"blocking-transferability-of-adversarial","title":"Blocking Transferability of Adversarial Examples in Black-Box Learning Systems","date":"2017-03-13","arxiv_id":"1703.04318","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature-selection-based-on-pca-and-pso-for","title":"Feature Selection based on PCA and PSO for Multimodal Medical Image Fusion using DTCWT","date":"2017-01-31","arxiv_id":"1701.08918","repositories_listed":0,"syntology":null},{"url":null,"slug":"weak-adaptive-submodularity-and-group-based","title":"Weak Adaptive Submodularity and Group-Based Active Diagnosis with Applications to State Estimation with Persistent Sensor Faults","date":"2017-01-24","arxiv_id":"1701.06731","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-sp-theory-of-intelligence-as-a-foundation","title":"The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine","date":"2016-12-22","arxiv_id":"1612.07555","repositories_listed":0,"syntology":null},{"url":null,"slug":"segmentation-of-large-images-based-on-super","title":"Segmentation of large images based on super-pixels and community detection in graphs","date":"2016-12-12","arxiv_id":"1612.03705","repositories_listed":0,"syntology":null},{"url":null,"slug":"vaidya-a-spoken-dialog-system-for-health","title":"Vaidya: A Spoken Dialog System for Health Domain","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"new-trends-in-neutrosophic-theory-and","title":"New Trends in Neutrosophic Theory and Applications","date":"2016-11-23","arxiv_id":"1611.08555","repositories_listed":0,"syntology":null},{"url":null,"slug":"stacked-autoencoders-for-medical-image-search","title":"Stacked Autoencoders for Medical Image Search","date":"2016-10-02","arxiv_id":"1610.00320","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-probabilistic-network-for-the-diagnosis-of","title":"A probabilistic network for the diagnosis of acute cardiopulmonary diseases","date":"2016-09-22","arxiv_id":"1609.06864","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-trends-for-focal-brain","title":"Deep learning trends for focal brain pathology segmentation in MRI","date":"2016-07-18","arxiv_id":"1607.05258","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimating-uncertainty-online-against-an","title":"Estimating Uncertainty Online Against an Adversary","date":"2016-07-13","arxiv_id":"1607.03594","repositories_listed":0,"syntology":null},{"url":null,"slug":"performance-based-evaluation-of-various","title":"Performance Based Evaluation of Various Machine Learning Classification Techniques for Chronic Kidney Disease Diagnosis","date":"2016-06-28","arxiv_id":"1606.09581","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiscale-segmentation-via-bregman-distances","title":"Multiscale Segmentation via Bregman Distances and Nonlinear Spectral Analysis","date":"2016-04-22","arxiv_id":"1604.06665","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-neutrosophic-recommender-system-for-medical","title":"A Neutrosophic Recommender System for Medical Diagnosis Based on Algebraic Neutrosophic Measures","date":"2016-02-25","arxiv_id":"1602.08447","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-utility-of-abstaining-in-binary","title":"The Utility of Abstaining in Binary Classification","date":"2015-12-26","arxiv_id":"1512.08133","repositories_listed":0,"syntology":null},{"url":null,"slug":"anchored-discrete-factor-analysis","title":"Anchored Discrete Factor Analysis","date":"2015-11-10","arxiv_id":"1511.03299","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluation-of-joint-multi-instance-multi","title":"Evaluation of Joint Multi-Instance Multi-Label Learning For Breast Cancer Diagnosis","date":"2015-10-10","arxiv_id":"1510.02942","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-image-classification-via-svm-using","title":"Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data","date":"2015-09-15","arxiv_id":"1509.04619","repositories_listed":0,"syntology":null},{"url":null,"slug":"proposal-for-the-creation-of-a-research","title":"Proposal for the creation of a research facility for the development of the SP machine","date":"2015-08-19","arxiv_id":"1508.04570","repositories_listed":0,"syntology":null},{"url":null,"slug":"extracting-disease-symptom-relationships-by","title":"Extracting Disease-Symptom Relationships by Learning Syntactic Patterns from Dependency Graphs","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"releaf-an-algorithm-for-learning-and","title":"RELEAF: An Algorithm for Learning and Exploiting Relevance","date":"2015-02-05","arxiv_id":"1502.01418","repositories_listed":0,"syntology":null},{"url":null,"slug":"discovering-learning-and-exploiting-relevance","title":"Discovering, Learning and Exploiting Relevance","date":"2014-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-variational-bayesian-approximations","title":"Sparse Variational Bayesian Approximations for Nonlinear Inverse Problems: applications in nonlinear elastography","date":"2014-12-01","arxiv_id":"1412.0473","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-diagnosis-as-pattern-recognition-in-a","title":"Medical diagnosis as pattern recognition in a framework of information compression by multiple alignment, unification and search","date":"2014-09-29","arxiv_id":"1409.8053","repositories_listed":0,"syntology":null},{"url":null,"slug":"ambiguity-driven-fuzzy-c-means-clustering-how","title":"Ambiguity-Driven Fuzzy C-Means Clustering: How to Detect Uncertain Clustered Records","date":"2014-09-09","arxiv_id":"1409.2821","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-extraction-from-german-patient","title":"Information Extraction from German Patient Records via Hybrid Parsing and Relation Extraction Strategies","date":"2014-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"smart-machines-and-the-sp-theory-of","title":"Smart machines and the SP theory of intelligence","date":"2014-01-08","arxiv_id":"1401.1669","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-continuity-of-images-by-transmission","title":"The Continuity of Images by Transmission Imaging Revisited","date":"2014-01-08","arxiv_id":"1401.1558","repositories_listed":0,"syntology":null},{"url":null,"slug":"performance-analysis-of-neural-network-models","title":"Performance Analysis Of Neural Network Models For Oxazolines And Oxazoles Derivatives Descriptor Dataset","date":"2013-12-10","arxiv_id":"1312.2853","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-white-blood-cell-measuring-aid-for","title":"Automatic White Blood Cell Measuring Aid for Medical Diagnosis","date":"2013-12-03","arxiv_id":"1312.0809","repositories_listed":0,"syntology":null},{"url":null,"slug":"test-set-selection-using-active-information","title":"Test Set Selection using Active Information Acquisition for Predictive Models","date":"2013-12-03","arxiv_id":"1312.0790","repositories_listed":0,"syntology":null},{"url":null,"slug":"natural-language-query-refinement-for-problem","title":"Natural Language Query Refinement for Problem Resolution from Crowd-Sourced Semi-Structured Data","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"a140fcb50987f1bc0b30df2aa0f921fcfb084131c1cb82983cf252d05c598b8f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}