Segmentation, trace denoising and spike extraction framework. by Changjia Cai (10647521)

Flowchart of software workflow. by Gavrielle R. Untracht (11820311)

Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX by Umesh C. Sharma (10785063)

“…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …”

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…<pre>Figures at Thesis_RAMIS/Figs_PI related with PhD Thesis:<br><br>AN INFORMATION-THEORETIC SAMPLING STRATEGY FOR THE RECOVERY OF GEOLOGICAL IMAGES: MODELING, ANALYSIS, AND IMPLEMENTATION<br><br>Data for the <a href="https://github.com/fsantibanezleal/FASL_Thesis_RAMIS" rel="noreferrer" target="_blank">LaTeX </a>version of the document<br><br>In this thesis the role of preferential sampling has been systematically addressed for the task of geological facies recovery using multiple-point simulation (\emph{<i>MPS</i>}) and for the problem of short-term planning in mining.  …”

An AI-based Ecosystem for Real-time Gravitational Wave Analyses by Erik Katsavounidis (19369348)

“…ML4GW, HERMES and the entire ecosystem can quickly integrate the plethora of deep learning based algorithms being developed for gravitational wave identification across the broader astrophysics community.…”

DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx by Jun Zhang (48506)

“…The ResNet-50 architectural model was used to implement deep transfer learning (DTL), undergoing -pre-training separately on the RadImageNet and ImageNet datasets. …”

DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx by Yuhong Huang (115702)

“…The molecular subtypes and AR expression in pre-treatment biopsy specimens were assessed. A total of 4,198 radiomics features were extracted from the pre-biopsy multi-parametric MRI (including dynamic contrast-enhancement T1-weighted images, fat-suppressed T2-weighted images, and apparent diffusion coefficient map) of each patient. …”

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

Data_Sheet_1_Machine Learning Classifiers to Evaluate Data From Gait Analysis With Depth Cameras in Patients With Parkinson’s Disease.docx by Beatriz Muñoz-Ospina (12564505)

“…The CIM shows a relation between leg variables and the arms swing asymmetry (ASA) and a proportional relationship between ASA and the diagnosis of PD with a robust estimator (1,537).</p>Conclusions<p>Machine learning techniques based on objective measures using portable low-cost devices (Kinect^®eMotion) are useful and accurate to classify patients with Parkinson’s disease. …”

Code by Baoqiang Chen (21099509)

“…</p><p><br></p><p dir="ltr">This architecture was implemented using the PyTorch library and trained using cross-entropy loss. The model was optimized to classify RNA sequences, achieving robust performance across multiple test sets.…”

Core data by Baoqiang Chen (21099509)

“…</p><p><br></p><p dir="ltr">This architecture was implemented using the PyTorch library and trained using cross-entropy loss. The model was optimized to classify RNA sequences, achieving robust performance across multiple test sets.…”

DataSheet1_Removing the Bottleneck: Introducing cMatch - A Lightweight Tool for Construct-Matching in Synthetic Biology.PDF by Alexis Casas (11924822)

“…<p>We present a software tool, called cMatch, to reconstruct and identify synthetic genetic constructs from their sequences, or a set of sub-sequences—based on two practical pieces of information: their modular structure, and libraries of components. …”