Inside Rochester’s Deep Rock Tunnel Network
Apr 11, 2015 · By Mike Governale A few weeks ago we took you on a trip to Van Lare Wastewater Treatment Facility to see where Rochester’s dirty water goes to get cleaned up. It was there that we …
Estimating Motor Symptom Presence and Severity in Parkinson's Disease from Wrist Accelerom…
Parkinson's disease (PD) is a neurodegenerative condition characterized by frequently changing motor symptoms, necessitating continuous symptom monitoring for more targeted treatment. Classical time series classification and deep learning techniques...
Deep Learning-based Prediction of Clinical Trial Enrollment with Uncertainty Estimates
Clinical trials are a systematic endeavor to assess the safety and efficacy of new drugs or treatments. Conducting such trials typically demands significant financial investment and meticulous planning, highlighting the need for accurate predictions...
Distributed Representation for Traditional Chinese Medicine Herb via Deep Learning Models
Traditional Chinese Medicine (TCM) has accumulated a big amount of precious resource in the long history of development. TCM prescriptions that consist of TCM herbs are an important form of TCM treatment, which are similar to natural language documen...
Bots Don't Sit Still: A Longitudinal Study of Bot Behaviour Change, Temporal Drift, and Fe…
Social bots are now deeply embedded in online platforms for promotion, persuasion, and manipulation. Most bot-detection systems still treat behavioural features as static, implicitly assuming bots behave stationarily over time. We test that assumptio...
Cholesteatoma Ear Cysts: Symptoms, Diagnosis, Treatment - WebMD
Jan 25, 2025 · Sometimes, skin cells inside your ear can do this and cause a lump called a cholesteatoma. The lump typically starts deep in your ear near your eardrum and grows toward your …
FruitProm: Probabilistic Maturity Estimation and Detection of Fruits and Vegetables
Maturity estimation of fruits and vegetables is a critical task for agricultural automation, directly impacting yield prediction and robotic harvesting. Current deep learning approaches predominantly treat maturity as a discrete classification proble...
Multiclass Spinal Cord Tumor Segmentation on MRI with Deep Learning
Spinal cord tumors lead to neurological morbidity and mortality. Being able to obtain morphometric quantification (size, location, growth rate) of the tumor, edema, and cavity can result in improved monitoring and treatment planning. Such quantificat...
Multi-modal deep learning system for depression and anxiety detection
Traditional screening practices for anxiety and depression pose an impediment to monitoring and treating these conditions effectively. However, recent advances in NLP and speech modelling allow textual, acoustic, and hand-crafted language-based featu...
Fully Automated Organ Segmentation in Male Pelvic CT Images
Accurate segmentation of prostate and surrounding organs at risk is important for prostate cancer radiotherapy treatment planning. We present a fully automated workflow for male pelvic CT image segmentation using deep learning. The architecture consi...
Inside Rochester’s Deep Rock Tunnel Network
Apr 11, 2015 · By Mike Governale A few weeks ago we took you on a trip to Van Lare Wastewater Treatment Facility to see where Rochester’s dirty water goes to get cleaned up. It was there that we …
BSEL-UC3M/DLUS
GitHub repository for DLUS: Deep Learning-based Segmentation of Prostatic Urethra on Computed Tomography Scans for Treatment Planning (⭐ 1)
Deep Discriminative Fine-Tuning for Cancer Type Classification
Determining the primary site of origin for metastatic tumors is one of the open problems in cancer care because the efficacy of treatment often depends on the cancer tissue of origin. Classification methods that can leverage tumor genomic data and pr...
Lucy-SKG: Learning to Play Rocket League Efficiently Using Deep Reinforcement Learning
A successful tactic that is followed by the scientific community for advancing AI is to treat games as problems, which has been proven to lead to various breakthroughs. We adapt this strategy in order to study Rocket League, a widely popular but rath...
Deep Lesion Tracker: Monitoring Lesions in 4D Longitudinal Imaging Studies
Monitoring treatment response in longitudinal studies plays an important role in clinical practice. Accurately identifying lesions across serial imaging follow-up is the core to the monitoring procedure. Typically this incorporates both image and ana...
C-arm Guidance: A Self-supervised Approach To Automated Positioning During Stroke Thrombec…
Thrombectomy is one of the most effective treatments for ischemic stroke, but it is resource and personnel-intensive. We propose employing deep learning to automate critical aspects of thrombectomy, thereby enhancing efficiency and safety. In this wo...
MBDRes-U-Net: Multi-Scale Lightweight Brain Tumor Segmentation Network
Accurate segmentation of brain tumors plays a key role in the diagnosis and treatment of brain tumor diseases. It serves as a critical technology for quantifying tumors and extracting their features. With the increasing application of deep learning m...
Label-free virtual HER2 immunohistochemical staining of breast tissue using deep learning
The immunohistochemical (IHC) staining of the human epidermal growth factor receptor 2 (HER2) biomarker is widely practiced in breast tissue analysis, preclinical studies and diagnostic decisions, guiding cancer treatment and investigation of pathoge...
Interpretable HER2 scoring by evaluating clinical Guidelines through a weakly supervised,…
The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important prognostic biomarker for breast cancer treatment selection. However, HER2 scoring has notoriously high interobserver variability due to stain variations...
Restore Anything Pipeline: Segment Anything Meets Image Restoration
Recent image restoration methods have produced significant advancements using deep learning. However, existing methods tend to treat the whole image as a single entity, failing to account for the distinct objects in the image that exhibit individual...