AIMC Topic: Humans

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Subchondral Bone Length in Knee Osteoarthritis: A Deep Learning-Derived Imaging Measure and Its Association With Radiographic and Clinical Outcomes.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: To develop a bone shape measure that reflects the extent of cartilage loss and bone flattening in knee osteoarthritis (OA) and test it against estimates of disease severity.

A Smart Capacitive Sensor Skin with Embedded Data Quality Indication for Enhanced Safety in Human-Robot Interaction.

Sensors (Basel, Switzerland)
Smart sensors are an integral part of the Fourth Industrial Revolution and are widely used to add safety measures to human-robot interaction applications. With the advancement of machine learning methods in resource-constrained environments, smart se...

Predicting physiological aging rates from a range of quantitative traits using machine learning.

Aging
It is widely thought that individuals age at different rates. A method that measures "physiological age" or physiological aging rate independent of chronological age could therefore help elucidate mechanisms of aging and inform an individual's risk o...

Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study.

Scientific reports
The placebo effect across psychiatric disorders is still not well understood. In the present study, we conducted meta-analyses including meta-regression, and machine learning analyses to investigate whether the power of placebo effect depends on the ...

Deep learning-based thin-section MRI reconstruction improves tumour detection and delineation in pre- and post-treatment pituitary adenoma.

Scientific reports
Even a tiny functioning pituitary adenoma could cause symptoms; hence, accurate diagnosis and treatment are crucial for management. However, it is difficult to diagnose a small pituitary adenoma using conventional MR sequence. Deep learning-based rec...

3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients.

Nature communications
Cochlear implants restore hearing in patients with severe to profound deafness by delivering electrical stimuli inside the cochlea. Understanding stimulus current spread, and how it correlates to patient-dependent factors, is hampered by the poor acc...

adabmDCA: adaptive Boltzmann machine learning for biological sequences.

BMC bioinformatics
BACKGROUND: Boltzmann machines are energy-based models that have been shown to provide an accurate statistical description of domains of evolutionary-related protein and RNA families. They are parametrized in terms of local biases accounting for resi...

Deep learning-based thoracic CBCT correction with histogram matching.

Biomedical physics & engineering express
Kilovoltage cone-beam computed tomography (CBCT)-based image-guided radiation therapy (IGRT) is used for daily delivery of radiation therapy, especially for stereotactic body radiation therapy (SBRT), which imposes particularly high demands for setup...

Association of Individual and Community Factors With Hepatitis C Infections Among Pregnant People and Newborns.

JAMA health forum
IMPORTANCE: The opioid crisis has increasingly affected pregnant people and infants. Hepatitis C virus (HCV) infections, a known complication of opioid use, grew in parallel with opioid-related complications; however, the literature informing individ...

PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis.

Frontiers in public health
COVID-19 is a sort of infectious disease caused by a new strain of coronavirus. This study aims to develop a more accurate COVID-19 diagnosis system. First, the -conv module (nCM) is introduced. Then we built a 12-layer convolutional neural network...