![](https://dblp.uni-trier.de./img/logo.ua.320x120.png)
![](https://dblp.uni-trier.de./img/dropdown.dark.16x16.png)
![](https://dblp.uni-trier.de./img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.uni-trier.de./img/search.dark.16x16.png)
![search dblp](https://dblp.uni-trier.de./img/search.dark.16x16.png)
default search action
22nd AIME 2024: Salt Lake City, UT, USA - Part I
- Joseph Finkelstein
, Robert Moskovitch
, Enea Parimbelli
:
Artificial Intelligence in Medicine - 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9-12, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14844, Springer 2024, ISBN 978-3-031-66537-0
Predictive Modelling and Disease Risk Prediction
- Po-Kuang Chen, Shih-Hsien Sung, Ling Chen:
Applying Gaussian Mixture Model for Clustering Analysis of Emergency Room Patients Based on Intubation Status. 3-10 - Laurent Vouriot, Stanislas Rebaudet, Jean Gaudart, Raquel Ureña:
Bayesian Neural Network to Predict Antibiotic Resistance. 11-16 - András Millinghoffer, Mátyás Antal, Márk Marosi, András Formanek, András Antos, Péter Antal:
Boosting Multitask Decomposition: Directness, Sequentiality, Subsampling, Cross-Gradients. 17-35 - Brian W. Locke
, W. Wayne Richards, Jeanette P. Brown
, Wanting Cui
, Joseph Finkelstein
, Krishna M. Sundar
, Ramkiran Gouripeddi
:
Diagnostic Modeling to Identify Unrecognized Inpatient Hypercapnia Using Health Record Data. 36-45 - Xiangru Chen
, Milos Hauskrecht
:
Enhancing Hypotension Prediction in Real-Time Patient Monitoring Through Deep Learning: A Novel Application of XResNet with Contrastive Learning and Value Attention Mechanisms. 46-51 - Josip Grguric, Annette ten Teije, Frank van Harmelen:
Evaluating the TMR Model for Multimorbidity Decision Support Using a Community-of-Practice Based Methodology. 52-63 - Beatriz López
, David Galera, Abel López-Bermejo
, Judit Bassols
:
Frequent Patterns of Childhood Overweight from Longitudinal Data on Parental and Early-Life of Infants Health. 64-69 - Paulo Vitor de Campos Souza, Mauro Dragoni:
Fuzzy Neural Network Model Based on Uni-Nullneuron in Extracting Knowledge About Risk Factors of Maternal Health. 70-75 - Shiwei Lin, Shiqiang Tao, Yan Huang, Xiaojin Li, Guo-Qiang Zhang:
Identifying Factors Associated with COVID-19 All-Cause 90-Day Readmission: Machine Learning Approaches. 76-80 - Syed Hamail Hussain Zaidi
, Amna Basharat, Muddassar Farooq:
Mining Disease Progression Patterns for Advanced Disease Surveillance. 81-89 - Ben Kurzion, Chia-Hao Shih
, Hong Xie, Xin Wang
, Kevin S. Xu
:
Minimizing Survey Questions for PTSD Prediction Following Acute Trauma. 90-100 - Zuzanna Wójcik
, Vania Dimitrova
, Lorraine Warrington
, Galina Velikova
, Kate Absolom
:
Patient-Centric Approach for Utilising Machine Learning to Predict Health-Related Quality of Life Changes During Chemotherapy. 101-116 - Ladislav Floris, Daniel Vasata
:
Predicting Blood Glucose Levels with LMU Recurrent Neural Networks: A Novel Computational Model. 117-127 - Chiara Dachena
, Roberto Gatta
, Mariachiara Savino
, Stefania Orini
, Nicola Acampora
, M. Letizia Serra, Stefano Patarnello, Christian Barillaro
, Carlotta Masciocchi
:
Prediction Modelling and Data Quality Assessment for Nursing Scale in a Big Hospital: A Proposal to Save Resources and Improve Data Quality. 128-137 - Tobias Kropp
, Shiva Faeghi
, Kunibert Lennerts
:
Process Mining for Capacity Planning and Reconfiguration of a Logistics System to Enhance the Intra-Hospital Patient Transport. Case Study. 138-150 - Paul Dubois
, Paul-Henry Cournède
, Nikos Paragios
, Pascal Fenoglietto:
Radiotherapy Dose Optimization via Clinical Knowledge Based Reinforcement Learning. 151-160 - Zhilin Lu, Jingming Liu, Ruihong Luo, Chunping Li:
Reinforcement Learning with Balanced Clinical Reward for Sepsis Treatment. 161-171 - Corinne G. Allaart, Marc X. Makkes, Lea Dijksman, Paul van der Nat, Douwe Biesma, Henri E. Bal, Aart van Halteren:
Secure and Private Vertical Federated Learning for Predicting Personalized CVA Outcomes. 172-181 - Amila Kugic
, Akhila Abdulnazar
, Anto Knezovic, Stefan Schulz
, Markus Kreuzthaler
:
Smoking Status Classification: A Comparative Analysis of Machine Learning Techniques with Clinical Real World Data. 182-191 - Bikram De, Mykhailo Sakevych, Vangelis Metsis
:
The Impact of Data Augmentation on Time Series Classification Models: An In-Depth Study with Biomedical Data. 192-203 - Minakshi Debnath
, Md Shahriar Kabir
, Jianyuan Ni
, Anne Hee Hiong Ngu
:
The Impact of Synthetic Data on Fall Detection Application. 204-209
Natural Language Processing
- Saba Ghanbari Haez, Marina Segala, Patrizio Bellan, Simone Magnolini, Leonardo Sanna, Monica Consolandi, Mauro Dragoni:
A Retrieval-Augmented Generation Strategy to Enhance Medical Chatbot Reliability. 213-223 - Chia-Hsuan Chang
, Mary M. Lucas
, Yeawon Lee
, Christopher C. Yang
, Grace Lu-Yao
:
Beyond Self-consistency: Ensemble Reasoning Boosts Consistency and Accuracy of LLMs in Cancer Staging. 224-228 - Paloma Rabaey
, Johannes Deleu, Stefan Heytens
, Thomas Demeester
:
Clinical Reasoning over Tabular Data and Text with Bayesian Networks. 229-250 - Deepak Gupta
, Dina Demner-Fushman
:
Empowering Language Model with Guided Knowledge Fusion for Biomedical Document Re-ranking. 251-260 - Regina Ofori-Boateng
, Magaly Aceves-Martins
, Nirmalie Wiratunga
, Carlos Francisco Moreno-García
:
Enhancing Abstract Screening Classification in Evidence-Based Medicine: Incorporating Domain Knowledge into Pre-trained Models. 261-272 - Xubing Hao
, Rashmie Abeysinghe
, Jay Shi, Licong Cui
:
Exploring Pre-trained Language Models for Vocabulary Alignment in the UMLS. 273-278 - Ortal Hirszowicz, Dvir Aran:
ICU Bloodstream Infection Prediction: A Transformer-Based Approach for EHR Analysis. 279-292 - Saurabh Mathur, Veerendra P. Gadekar, Rashika Ramola, Peixin Wang, Ramachandran Thiruvengadam, David M. Haas, Shinjini Bhatnagar, Nitya Wadhwa, Garbhini Study Group, Predrag Radivojac, Himanshu Sinha, Kristian Kersting, Sriraam Natarajan:
Modeling Multiple Adverse Pregnancy Outcomes: Learning from Diverse Data Sources. 293-302 - Yaoqian Sun
, Dan Wu
, Zikang Chen
, Hailing Cai
, Jiye An
:
OptimalMEE: Optimizing Large Language Models for Medical Event Extraction Through Fine-Tuning and Post-hoc Verification. 303-311 - Waheed Ahmed Abro
, Hanane Kteich
, Zied Bouraoui
:
Self-supervised Segment Contrastive Learning for Medical Document Representation. 312-321 - Brian D. Ondov
, Dina Demner-Fushman
:
Sentence-Aligned Simplification of Biomedical Abstracts. 322-333 - Vishakha Sharma, Andreas Thalhammer, Amila Kugic
, Stefan Schulz
, Markus Kreuzthaler
:
Sequence-Model-Based Medication Extraction from Clinical Narratives in German. 334-344 - Seibi Kobara
, Alireza Rafiei
, Masoud Nateghi
, Selen Bozkurt
, Rishikesan Kamaleswaran
, Abeed Sarker
:
Social Media as a Sensor: Analyzing Twitter Data for Breast Cancer Medication Effects Using Natural Language Processing. 345-354
Bioinformatics and Omics
- Joung Min Choi
, Liqing Zhang:
Breast Cancer Subtype Prediction Model Integrating Domain Adaptation with Semi-supervised Learning on DNA Methylation Profiles. 357-366 - Mohsen Nabian, Zahra Eftekhari, Chi Wah Wong:
CI-VAE for Single-Cell: Leveraging Generative-AI to Enhance Disease Understanding. 367-372 - Yiqing Shen
, Outongyi Lv, Houying Zhu, Yu Guang Wang:
ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering. 373-383
Wearable Devices, Sensors, and Robotics
- Tahsin Kazi
, John Oakley
, Anh Duong
, El Arbi Belfasi
, Katherine H. Ingram
, Maria Valero
:
Advancements in Non-invasive AI-Powered Glucose Monitoring: Leveraging Multispectral Imaging Across Diverse Wavelengths. 387-396 - Marina Andric, Mauro Dragoni, Francesco Ricci:
Anticipating Stress: Harnessing Biomarker Signals from a Wrist-Worn Device for Early Prediction. 397-408 - Abrar S. Alrumayh, Chiu C. Tan:
Improving Reminder Apps for Home Voice Assistants. 409-413
![](https://dblp.uni-trier.de./img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.