AIMC Topic: Proof of Concept Study
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Predicting first session working alliances using deep learning algorithms: A proof-of-concept study for personalized psychotherapy.
Psychotherapy research : journal of the Society for Psychotherapy Research
May 30, 2022
OBJECTIVE: The aim of this proof-of-concept study is to develop a predictive model based on deep learning algorithms to predict working alliances after the first therapeutic session and to provide a basis for clinical decisions.
Utilization of deep learning to quantify fluid volume of neovascular age-related macular degeneration patients based on swept-source OCT imaging: The ONTARIO study.
PloS one
Feb 14, 2022
PURPOSE: To evaluate the predictive ability of a deep learning-based algorithm to determine long-term best-corrected distance visual acuity (BCVA) outcomes in neovascular age-related macular degeneration (nARMD) patients using baseline swept-source o...
Proof of concept study for using UR10 robot to help total hip replacement.
The international journal of medical robotics + computer assisted surgery : MRCAS
Dec 30, 2021
BACKGROUND: The demand for total hip replacement (THR) for treating osteoarthritis has grown substantially worldwide. The existing robotic systems used in THR are invasive and costly. This study aims to develop a less-invasive and low-cost robotic sy...
Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer.
The Journal of pathology
Dec 28, 2021
The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomar...
Reproducibility of Results
Risk Factors
Colorectal Neoplasms
Humans
Retrospective Studies
Lymph Nodes
Lymphatic Metastasis
Early Detection of Cancer
Adipose Tissue
Risk Assessment
Diagnosis, Computer-Assisted
Deep Learning
Microscopy
Image Interpretation, Computer-Assisted
Proof of Concept Study
Predictive Value of Tests
Neoplasm Staging
Biopsy
Deep learning-based 3Ddose reconstruction with an electronic portal imaging device for magnetic resonance-linear accelerators: a proof of concept study.
Physics in medicine and biology
Dec 2, 2021
To develop a novel deep learning-based 3Ddose reconstruction framework with an electronic portal imaging device (EPID) for magnetic resonance-linear accelerators (MR-LINACs).The proposed method directly back-projected 2D portal dose into 3D patient c...
Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study.
The Lancet. Digital health
Nov 15, 2021
BACKGROUND: Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide patient management, but it is one of the most challenging areas of pathology, requiring considerable e...
Automatic Identification of Papillary Projections in Indeterminate Biliary Strictures Using Digital Single-Operator Cholangioscopy.
Clinical and translational gastroenterology
Oct 27, 2021
INTRODUCTION: Characterization of biliary strictures is challenging. Papillary projections (PP) are often reported in biliary strictures with high malignancy potential during digital single-operator cholangioscopy. In recent years, the development of...
A multisystem-compatible deep learning-based algorithm for detection and characterization of angiectasias in small-bowel capsule endoscopy. A proof-of-concept study.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Sep 22, 2021
BACKGROUND AND AIMS: Current artificial intelligence (AI)-based solutions for capsule endoscopy (CE) interpretation are proprietary. We aimed to evaluate an AI solution trained on a specific CE system (Pillcam®, Medtronic) for the detection of angiec...
Learning, visualizing and exploring 16S rRNA structure using an attention-based deep neural network.
PLoS computational biology
Sep 22, 2021
Recurrent neural networks with memory and attention mechanisms are widely used in natural language processing because they can capture short and long term sequential information for diverse tasks. We propose an integrated deep learning model for micr...
Deep Learning-Based Automated Thrombolysis in Cerebral Infarction Scoring: A Timely Proof-of-Principle Study.
Stroke
Sep 9, 2021
BACKGROUND AND PURPOSE: Mechanical thrombectomy is an established procedure for treatment of acute ischemic stroke. Mechanical thrombectomy success is commonly assessed by the Thrombolysis in Cerebral Infarction (TICI) score, assigned by visual inspe...
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