AIMC Topic: Software

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Rejoinder to Discussions on "Approval policies for modifications to machine learning-based software as a medical device: A study of bio-creep".

Biometrics
We thank the discussants for sharing their unique perspectives on the problem of designing automatic algorithm change protocols (aACPs) for machine learning-based software as a medical device. Both Pennello et al. and Rose highlighted a number of cha...

Discussion on "Approval policies for modifications to machine learning-based software as a medical device: A study of biocreep" by Jean Feng, Scott Emerson, and Noah Simon.

Biometrics
I applaud the authors of Feng (2020) for tackling a challenging statistical problem on approval policies for software as a medical device (SaMD). Their work exploring methodology that could autonomously build algorithmic change protocols soundly ext...

Approval policies for modifications to machine learning-based software as a medical device: A study of bio-creep.

Biometrics
Successful deployment of machine learning algorithms in healthcare requires careful assessments of their performance and safety. To date, the FDA approves locked algorithms prior to marketing and requires future updates to undergo separate premarket ...

Fake metabolomics chromatogram generation for facilitating deep learning of peak-picking neural networks.

Journal of bioscience and bioengineering
Finding peaks in chromatograms and determining their start and end points (peak picking) is a core task in chromatography based biotechnology. Construction of peak-picking neural networks by deep learning was, however, hampered from the preparation o...

Automated and accurate segmentation of leaf venation networks via deep learning.

The New phytologist
Leaf vein network geometry can predict levels of resource transport, defence and mechanical support that operate at different spatial scales. However, it is challenging to quantify network architecture across scales due to the difficulties both in se...

CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence.

EBioMedicine
BACKGROUND: Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's pr...

Advancements in sex estimation using the diaphyseal cross-sectional geometric properties of the lower and upper limbs.

International journal of legal medicine
This paper introduces an automated method for estimating sex from the lower and upper limbs based on diaphyseal CSG properties. The proposed method was developed and evaluated using 389 femurs, 412 tibias, and 404 humeri of adult individuals from a m...

Use of artificial intelligence for tailored routine urine analyses.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
OBJECTIVES: Urine is the most common material tested in clinical microbiology laboratories. Automated analysis is already performed, permitting quicker results and decreasing the laboratory technologist's (LT) workload. These automatic systems have i...

Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance.

Scientific reports
Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is chall...