Research & publications

launching — first Atlanta meetup this fall, join the list →free worksheets — prompt engineering, computer vision, ML metrics →for companies — team training and event sponsorship →NVIDIA-certified — generative-AI workshops in partnership with NVIDIA →open source — RocketRAG, UMIE, LOMA on GitHub, contributors welcome →

// publications

Researchat the clinic edge.

We conduct research at the intersection of artificial intelligence, healthcare, and natural language processing — bridging theory and real-world clinical impact.

15papers

66citations

37conferences

RAD-SRAC: Simple Retrieval Augmented Classification for Radiology
Barbara Klaudel, Aleksander Obuchowski · AAAI 2025 Workshop on GenAI4Health · 2025
Conversation Clustering Adaptation for Intent Recognition
Michał Lew, Aleksander Obuchowski, Emilia Kacprzak, Agnieszka Pluwak · 2021 IEEE International Conference on Machine Learning and Applications (ICMLA) · 2021
ColorNephroNet: Kidney Tumor Malignancy Prediction Using Medical Image Colorization
Aleksander Obuchowski, Barbara Klaudel, Roman Karski, Bartosz Rydziński, Mateusz Glembin, Paweł Syty, Patryk Jasik · The International FLAIRS Conference Proceedings · 2022
Predictors of Catheter-Induced Coronary and Aortic Dissections: A Machine Learning Approach
Barbara Klaudel, Jacek Klaudel, Michał Glaza, Wojciech Trenkner, Marek Szołkiewicz · JACC: Cardiovascular Interventions · 2021
Machine-Aided Detection of SARS-CoV-2 from Complete Blood Count
Barbara Klaudel, Aleksander Obuchowski, Małgorzata Dąbrowska, Kornelia Sałaga-Zaleska, Zdzisław Kowalczuk · Lecture Notes in Networks and Systems · 2021
COVID-19 Severity Forecast Based on Machine Learning and Complete Blood Count Data
Barbara Klaudel, Aleksander Obuchowski, Roman Karski, Bartosz Rydziński, Patryk Jasik, Zdzisław Kowalczuk · Lecture Notes in Networks and Systems · 2022
Transformer-Capsule Model for Intent Detection
Aleksander Obuchowski, Michał Lew · AAAI Conference on Artificial Intelligence · 2022
Information Extraction from Polish Radiology Reports Using Language Models
Aleksander Obuchowski, Barbara Klaudel, Patryk Jasik · EACL 2023 (BSNLP) · 2023
Explainable Machine Learning for Diffraction Patterns
Shabarish Nawaz, Vahid Rahmani, David Pennicard, Shankar Pala Ramakantha Setty, Barbara Klaudel, Heinz Graafsma · Journal of Applied Crystallography · 2023
Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in CT Analysis
Mateusz Glembin, Aleksander Obuchowski, Barbara Klaudel, Bartosz Rydziński, Roman Karski, Paweł Syty, Patryk Jasik, Wojciech J. Narożański · Medical Science Monitor · 2023
Target-Free Domain Adaptation through Cross-Adaptation
Aleksander Obuchowski, Barbara Klaudel, Piotr Frąckowski, Sebastian Krajna, Wasyl Badyra, Michał Czubenko, Zdzisław Kowalczuk · AAAI Conference on Artificial Intelligence · 2023
Catheter-Induced Coronary Artery and Aortic Dissections: Mechanisms and Risk Factors
Jacek Klaudel, Michał Glaza, Barbara Klaudel, Wojciech Trenkner, Krzysztof Pawłowski, Marek Szołkiewicz · Cardiology Journal · 2021
Assessing the Situation in the Face of Crisis
Agnieszka Pluwak, Emilia Kacprzak, Mateusz Stańczyk, Michał Lew, Aleksander Obuchowski · Social Network Analysis and Mining · 2022
Forewarned Is Forearmed: Machine Learning Algorithms for Prediction of Catheter-Induced Injuries
Jacek Klaudel, Barbara Klaudel, Michał Glaza, Wojciech Trenkner, Paweł Derejko, Marek Szołkiewicz · International Journal of Environmental Research and Public Health · 2021
Improving Intent Detection Accuracy Through Token-Level Labeling
Michał Lew, Aleksander Obuchowski, Marcin Kutyła · LDK 2021 · 2021

Researchat the clinic edge.

RAD-SRAC: Simple Retrieval Augmented Classification for Radiology

Conversation Clustering Adaptation for Intent Recognition

ColorNephroNet: Kidney Tumor Malignancy Prediction Using Medical Image Colorization

Predictors of Catheter-Induced Coronary and Aortic Dissections: A Machine Learning Approach

Machine-Aided Detection of SARS-CoV-2 from Complete Blood Count

COVID-19 Severity Forecast Based on Machine Learning and Complete Blood Count Data

Transformer-Capsule Model for Intent Detection

Information Extraction from Polish Radiology Reports Using Language Models

Explainable Machine Learning for Diffraction Patterns

Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in CT Analysis

Target-Free Domain Adaptation through Cross-Adaptation

Catheter-Induced Coronary Artery and Aortic Dissections: Mechanisms and Risk Factors

Assessing the Situation in the Face of Crisis

Forewarned Is Forearmed: Machine Learning Algorithms for Prediction of Catheter-Induced Injuries

Improving Intent Detection Accuracy Through Token-Level Labeling