AIMC Topic: Humans

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Automatic discovery of 100-miRNA signature for cancer classification using ensemble feature selection.

BMC bioinformatics
BACKGROUND: MicroRNAs (miRNAs) are noncoding RNA molecules heavily involved in human tumors, in which few of them circulating the human body. Finding a tumor-associated signature of miRNA, that is, the minimum miRNA entities to be measured for discri...

From manual to artificial intelligence fitting: Two cochlear implant case studies.

Cochlear implants international
To assess whether CI programming by means of a software application using artificial intelligence (AI), FOX®, may improve cochlear implant (CI) performance. Two adult CI recipients who had mixed auditory results with their manual fitting were selec...

Adversarial Examples: Opportunities and Challenges.

IEEE transactions on neural networks and learning systems
Deep neural networks (DNNs) have shown huge superiority over humans in image recognition, speech processing, autonomous vehicles, and medical diagnosis. However, recent studies indicate that DNNs are vulnerable to adversarial examples (AEs), which ar...

Machine learning for clinical decision support in infectious diseases: a narrative review of current applications.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
BACKGROUND: Machine learning (ML) is a growing field in medicine. This narrative review describes the current body of literature on ML for clinical decision support in infectious diseases (ID).

Essential Elements of Natural Language Processing: What the Radiologist Should Know.

Academic radiology
Natural language is ubiquitous in the workflow of medical imaging. Radiologists create and consume free text in their daily work, some of which can be amenable to enhancements through automatic processing. Recent advancements in deep learning and "ar...

Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI.

Medical image analysis
We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc approach that is trained using weakly annotated data (i.e., labels are available only at the image level without any lesion delineation). Our proposed post-hoc metho...

Bézier curve parametrisation and echo state network methods for solving optimal control problems of SIR model.

Bio Systems
In this work, we introduce an optimal control problem with two control variables of the SIR (susceptible-infected-recovered) epidemic model to minimise the infective and susceptible individuals. To solve the control problem, we use direct Bernstein-B...

EMG-based lumbosacral joint compression force prediction using a support vector machine.

Medical engineering & physics
Electromyography-assisted optimization (EMGAO) approach is widely used to predict lumbar joint loads under various dynamic and static conditions. However, such approach uses numerous anthropometric, kinematic, kinetic, and electromyographic data in t...

Augmented Bladder Tumor Detection Using Deep Learning.

European urology
Adequate tumor detection is critical in complete transurethral resection of bladder tumor (TURBT) to reduce cancer recurrence, but up to 20% of bladder tumors are missed by standard white light cystoscopy. Deep learning augmented cystoscopy may impro...