International Conference on Artificial Intelligence in Medicine

AIME

CORE rank

CORE rank (raw)

Fields of research

Applied Computing

Papers indexed

1,339

1989–2026

Best Applied Computing conferences

Papers per year

1989136 peak2026

Most published authors

AIME papers

1,339 records sourced from DBLP. Search titles, filter by year, sort by recency.

Year	Title	Authors
2019	An Automated Fall Detection System Using Recurrent Neural Networks.	Francisco Luna-Perejn, Javier Civit-Masot, Isabel Amaya-Rodriguez, Lourdes Duran-Lopez, Juan Pedro Dominguez-Morales, Antn Civit Balcells, Alejandro Linares-Barranco
2019	Deep Learning for Haemodialysis Time Series Classification.	Giorgio Leonardi, Stefania Montani, Manuel Striani
2019	Recent Context-Aware LSTM for Clinical Event Time-Series Prediction.	Jeongmin Lee, Milos Hauskrecht
2019	Evaluation of Random Forest and Ensemble Methods at Predicting Complications Following Cardiac Surgery.	Linda Lapp, Matt-Mouley Bouamrane, Kimberley Kavanagh, Marc Roper, David Young, Stefan Schraag
2019	Bayesian Network vs. Cox's Proportional Hazard Model of PAH Risk: A Comparison.	Jidapa Kraisangka, Marek J. Druzdzel, Lisa C. Lohmueller, Manreet K. Kanwar, James F. Antaki, Raymond L. Benza
2019	Local vs. Global Interpretability of Machine Learning Models in Type 2 Diabetes Mellitus Screening.	Leon Kopitar, Leona Cilar, Primoz Kocbek, Gregor Stiglic
2019	Explainable Machine Learning for Modeling of Early Postoperative Mortality in Lung Cancer.	Katarzyna Kobylinska, Tomasz Mikolajczyk, Mariusz Adamek, Tadeusz Orlowski, Przemyslaw Biecek
2019	Self-organizing Maps Using Acoustic Features for Prediction of State Change in Bipolar Disorder.	Olga Kaminska, Katarzyna Kaczmarek-Majer, Karol R. Opara, Wit Jakuczun, Monika Dominiak, Anna Antosik-Wjcinska, Lukasz Swiecicki, Olgierd Hryniewicz
2019	An Explainable Approach of Inferring Potential Medication Effects from Social Media Data.	Keyuan Jiang, Tingyu Chen, Liyuan Huang, Ravish Gupta, Ricardo A. Calix, Gordon R. Bernard
2019	Deep Learning Approach for Pathogen Detection Through Shotgun Metagenomics Sequence Classification.	Ying-Feng Hsu, Makiko Ito, Takumi Maruyama, Morito Matsuoka, Nicolas Jung, Yuki Matsumoto, Daisuke Motooka, Shota Nakamura
2019	A Machine Learning Approach to Predict Diabetes Using Short Recorded Photoplethysmography and Physiological Characteristics.	Chirath Hettiarachchi, Charith Chitraranjan
2019	Fully Interactive Lungs Auscultation with AI Enabled Digital Stethoscope.	Tomasz Grzywalski, Riccardo Belluzzo, Mateusz Piecuch, Marcin Szajek, Anna Breborowicz, Anna Pastusiak, Honorata Hafke-Dys, Jedrzej Kocinski
2019	Differential Diagnosis of Bacterial and Viral Meningitis Using Dominance-Based Rough Set Approach.	Ewelina Gowin, Jerzy Blaszczynski, Roman Slowinski, Jacek Wysocki, Danuta Januszkiewicz-Lewandowska
2019	Automatic Image-Derived Estimation of the Arterial Whole-Blood Input Function from Dynamic Cerebral PET with ^18 F-Choline.	Carlos Gonzlez, Pedro Bibiloni, Manuel Gonzlez Hidalgo, Arnau Mir, Sebasti Rub
2019	Towards Understanding ICU Treatments Using Patient Health Trajectories.	Alexander Galozy, Slawomir Nowaczyk, Anita Pinheiro Sant'Anna
2019	Identification of Patient Prescribing Predicting Cancer Diagnosis Using Boosted Decision Trees.	Josephine French, Cong Chen, Katherine Henson, Brian Shand, Patrick Ferris, Josh Pencheon, Sally Vernon, Meena Rafiq, David Howe, Georgios Lyratzopoulos, Jem Rashbass
2019	Automatic Alignment of Surgical Videos Using Kinematic Data.	Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Franois Petitjean, Lhassane Idoumghar, Pierre-Alain Muller
2019	Inferring Temporal Phenotypes with Topological Data Analysis and Pseudo Time-Series.	Arianna Dagliati, Nophar Geifman, Niels Peek, John H. Holmes, Lucia Sacchi, Seyed Erfan Sajjadi, Allan Tucker
2019	Pursuing Optimal Prediction of Discharge Time in ICUs with Machine Learning Methods.	David Cuadrado, David Riao, Josep Gmez, Mara Bod, Gonzalo Sirgo, Federico Esteban, Rafael Garca, Alejandro Rodrguez
2019	External Validation of a "Black-Box" Clinical Predictive Model in Nephrology: Can Interpretability Methods Help Illuminate Performance Differences?	Harry Freitas Da Cruz, Boris Pfahringer, Frederic Schneider, Alexander Meyer, Matthieu-P. Schapranow
2019	Unsupervised Mitral Valve Segmentation in Echocardiography with Neural Network Matrix Factorization.	Luca Corinzia, Jesse Provost, Alessandro Candreva, Maurizio Tamarasso, Francesco Maisano, Joachim M. Buhmann
2019	Common Misconceptions and Future Directions for AI in Medicine: A Physician-Data Scientist Perspective.	Anthony Chang
2019	Exploring Antimicrobial Resistance Prediction Using Post-hoc Interpretable Methods.	Bernardo Cnovas-Segura, Antonio Morales Nicols, Antonio Lpez Martnez-Carrasco, Manuel Campos, Jose M. Juarez, Luca Lpez-Rodrguez, Francisco Palacios
2019	Towards Health 4.0: e-Hospital Proposal Based Industry 4.0 and Artificial Intelligence Concepts.	Camilo Cceres, Joo Maurcio Rosrio, Dario Amaya
2019	A Data-Driven Exploration of Hypotheses on Disease Dynamics.	Marcos L. P. Bueno, Arjen Hommersom, Peter J. F. Lucas, Joost G. E. Janzing

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