AIMC Topic: Feasibility Studies

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A deep learning approach to evaluate the feasibility of enzymatic reactions generated by retrobiosynthesis.

Biotechnology journal
Retrobiosynthesis allows the designing of novel biosynthetic pathways for the production of chemicals and materials through metabolic engineering, but generates a large number of reactions beyond the experimental feasibility. Thus, an effective metho...

Robot-Assisted Carotid Artery Stenting: A Safety and Feasibility Study.

Cardiovascular and interventional radiology
PURPOSE: Endovascular robotics is an emerging technology within the developing field of medical robotics. This was a prospective evaluation to assess safety and feasibility of robotic-assisted carotid artery stenting.

Feasibility of automated planning for whole-brain radiation therapy using deep learning.

Journal of applied clinical medical physics
PURPOSE: The purpose of this study was to develop automated planning for whole-brain radiation therapy (WBRT) using a U-net-based deep-learning model for predicting the multileaf collimator (MLC) shape bypassing the contouring processes.

Reducing scan time of paediatric Tc-DMSA SPECT via deep learning.

Clinical radiology
AIM: To investigate the feasibility of reducing the scan time of paediatric technetium 99m (Tc) dimercaptosuccinic acid (DMSA) single-photon-emission computed tomographic (SPECT) using a deep learning (DL) method.

Recent advances in constraint and machine learning-based metabolic modeling by leveraging stoichiometric balances, thermodynamic feasibility and kinetic law formalisms.

Metabolic engineering
Understanding the governing principles behind organisms' metabolism and growth underpins their effective deployment as bioproduction chassis. A central objective of metabolic modeling is predicting how metabolism and growth are affected by both exter...

A deep learning diagnostic platform for diffuse large B-cell lymphoma with high accuracy across multiple hospitals.

Nature communications
Diagnostic histopathology is a gold standard for diagnosing hematopoietic malignancies. Pathologic diagnosis requires labor-intensive reading of a large number of tissue slides with high diagnostic accuracy equal or close to 100 percent to guide trea...

Discriminating pseudoprogression and true progression in diffuse infiltrating glioma using multi-parametric MRI data through deep learning.

Scientific reports
Differentiating pseudoprogression from true tumor progression has become a significant challenge in follow-up of diffuse infiltrating gliomas, particularly high grade, which leads to a potential treatment delay for patients with early glioma recurren...

Evaluation of the feasibility of an error-minimized approach to powered wheelchair skills training using shared control.

Disability and rehabilitation. Assistive technology
BACKGROUND: Powered wheelchairs promote participation for people with mobility limitations. For older adults with cognitive impairment, existing training methods may not address learning needs, leading to difficulty with powered wheelchair skills. Er...

The effect of PARO robotic seals for hospitalized patients with dementia: A feasibility study.

Geriatric nursing (New York, N.Y.)
Robotic seals have been studied in long-term care settings; though, no studies of patients with dementia in the acute care setting have been reported. The purpose of this study was to evaluate the feasibility of PARO interventions for hospitalized pa...

Machine learning to predict early TNF inhibitor users in patients with ankylosing spondylitis.

Scientific reports
We aim to generate an artificial neural network (ANN) model to predict early TNF inhibitor users in patients with ankylosing spondylitis. The baseline demographic and laboratory data of patients who visited Samsung Medical Center rheumatology clinic ...