31 – 40 of 359
- show: 10
- |
- sort: year (new to old)
Close
Embed this list
<iframe src=" "
width=" "
height=" "
allowtransparency="true"
frameborder="0">
</iframe>
- 2024
-
Mark
Efficacy assessment of an active tau immunotherapy in Alzheimer's disease patients with amyloid and tau pathology : a post hoc analysis of the “ADAMANT” randomised, placebo-controlled, double-blind, multi-centre, phase 2 clinical trial
(
- Contribution to journal › Article
-
Mark
A Simple End-to-End Computer-Aided Detection Pipeline for Trained Deep Learning Models
2024) 8th International Conference on Engineering of Computer-Based Systems, ECBS 2023 In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 14390 LNCS. p.259-262(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
-
Mark
A feasibility study of applying generative deep learning models for map labeling
(
- Contribution to journal › Article
-
Mark
On the right track? Energy use, carbon emissions, and intensities of world rail transportation, 1840–2020
(
- Contribution to journal › Article
-
Mark
Performance monitoring of kaplan turbine based hydropower plant under variable operating conditions using machine learning approach
(
- Contribution to journal › Article
-
Mark
Using machine learning to develop customer insights from user-generated content
(
- Contribution to journal › Article
-
Mark
Inter-Organizational Data Sharing Processes - An Exploratory Analysis of Incentives and Challenges
2024) 50th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2024 p.80-87(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
-
Mark
Epidemiology and evaluation of breathlessness - A data-driven approach
2024) In Lund University, Faculty of Medicine Doctoral Dissertation Series(
- Thesis › Doctoral thesis (compilation)
-
Mark
Improving hydrological modelling in cold regions using satellite remote sensing and machine learning techniques
2024)(
- Thesis › Doctoral thesis (compilation)
-
Mark
An explainable machine learning model to solid adnexal masses diagnosis based on clinical data and qualitative ultrasound indicators
(
- Contribution to journal › Article