AIMC Topic: Pilot Projects
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Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.
Rheumatology international
Jan 11, 2022
The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542 individuals with rheumatoid arthritis, or diabetes mellitu...
A pilot study of machine-learning based automated planning for primary brain tumours.
Radiation oncology (London, England)
Jan 6, 2022
PURPOSE: High-quality radiotherapy (RT) planning for children and young adults with primary brain tumours is essential to minimize the risk of late treatment effects. The feasibility of using automated machine-learning (ML) to aid RT planning in this...
Image quality and radiologists' subjective acceptance using model-based iterative and deep learning reconstructions as adjuncts to ultrahigh-resolution CT in low-dose contrast-enhanced abdominopelvic CT: phantom and clinical pilot studies.
Abdominal radiology (New York)
Dec 16, 2021
PURPOSE: In contrast-enhanced abdominopelvic CT (CE-APCT) for oncologic follow-up, ultrahigh-resolution CT (UHRCT) may improve depiction of fine lesions and low-dose scans are desirable for minimizing the potential adverse effects by ionizing radiati...
A New Socially Assistive Robot with Integrated Serious Games for Therapies with Children with Autism Spectrum Disorder and Down Syndrome: A Pilot Study.
Sensors (Basel, Switzerland)
Dec 16, 2021
This work introduces a new socially assistive robot termed MARIA T21 (meaning "Mobile Autonomous Robot for Interaction with Autistics", with the addition of the acronym T21, meaning "Trisomy 21", which is used to designate individuals with Down syndr...
The lesion detection efficacy of deep learning on automatic breast ultrasound and factors affecting its efficacy: a pilot study.
The British journal of radiology
Dec 15, 2021
OBJECTIVES: The aim of this study was to investigate the detection efficacy of deep learning (DL) for automatic breast ultrasound (ABUS) and factors affecting its efficacy.
Deciphering tumour tissue organization by 3D electron microscopy and machine learning.
Communications biology
Dec 13, 2021
Despite recent progress in the characterization of tumour components, the tri-dimensional (3D) organization of this pathological tissue and the parameters determining its internal architecture remain elusive. Here, we analysed the spatial organizatio...
Optical Biopsy Using a Neural Network to Predict Gene Expression From Photos of Wounds.
The Journal of surgical research
Nov 23, 2021
BACKGROUND: The clinical characterization of the biological status of complex wounds remains a considerable challenge. Digital photography provides a non-invasive means of obtaining wound information and is currently employed to assess wounds qualita...
Cancer classification using machine learning and HRV analysis: preliminary evidence from a pilot study.
Scientific reports
Nov 16, 2021
Most cancer patients exhibit autonomic dysfunction with attenuated heart rate variability (HRV) levels compared to healthy controls. This research aimed to create and evaluate a machine learning (ML) model enabling discrimination between cancer patie...
Prospective pilot study protocol evaluating the safety and feasibility of robot-assisted nipple-sparing mastectomy (RNSM).
BMJ open
Nov 15, 2021
INTRODUCTION: Nipple-sparing mastectomy (NSM) can be performed for the treatment of breast cancer and risk reduction, but total mammary glandular excision in NSM can be technically challenging. Minimally invasive robot-assisted NSM (RNSM) has the pot...
HoloMentor: A Novel Mixed Reality Surgical Anatomy Curriculum for Robot-Assisted Radical Prostatectomy.
European surgical research. Europaische chirurgische Forschung. Recherches chirurgicales europeennes
Nov 1, 2021
OBJECTIVES: The disruption to surgical training and medical education caused by the global COVID-19 pandemic highlighted the need for realistic, reliable, and engaging educational opportunities available outside of the operating theatre and accessibl...
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