AIMC Topic: Humans

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Stereotactic Neurosurgical Robotics With Real-Time Patient Tracking: A Cadaveric Study.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: Robotic neurosurgery may improve the accuracy, speed, and availability of stereotactic procedures. We recently developed a computer vision and artificial intelligence-driven frameless stereotaxy for nonimmobilized patients, creating an op...

The variant artificial intelligence easy scoring (VARIES) system.

Computers in biology and medicine
PURPOSE: Medical artificial intelligence (MAI) is artificial intelligence (AI) applied to the healthcare field. AI can be applied to many different aspects of genetics, such as variant classification. With little or no prior experience in AI coding, ...

Not just "big" data: Importance of sample size, measurement error, and uninformative predictors for developing prognostic models for digital interventions.

Behaviour research and therapy
There is strong interest in developing a more efficient mental health care system. Digital interventions and predictive models of treatment prognosis will likely play an important role in this endeavor. This article reviews the application of popular...

The Making of : Can We Produce Artificial Companions by Programming Sentience into Robots?

The New bioethics : a multidisciplinary journal of biotechnology and the body
This essay discusses sentient robot (SR) research through the lens of suffering. First three kinds of suffering are considered: physical, psychological, and existential. Physical pain is shown to be primarily subjective, and distinctive psychological...

Explainable multiview framework for dissecting spatial relationships from highly multiplexed data.

Genome biology
The advancement of highly multiplexed spatial technologies requires scalable methods that can leverage spatial information. We present MISTy, a flexible, scalable, and explainable machine learning framework for extracting relationships from any spati...

Two-year death prediction models among patients with Chagas Disease using machine learning-based methods.

PLoS neglected tropical diseases
Chagas disease (CD) is recognized by the World Health Organization as one of the thirteen most neglected tropical diseases. More than 80% of people affected by CD will not have access to diagnosis and continued treatment, which partly supports the hi...

Proposing Causal Sequence of Death by Neural Machine Translation in Public Health Informatics.

IEEE journal of biomedical and health informatics
Each year there are nearly 57 million deaths worldwide, with over 2.7 million in the United States. Timely, accurate and complete death reporting is critical for public health, especially during the COVID-19 pandemic, as institutions and government a...

COVID Detection From Chest X-Ray Images Using Multi-Scale Attention.

IEEE journal of biomedical and health informatics
Deep learning based methods have shown great promise in achieving accurate automatic detection of Coronavirus Disease (covid) - 19 from Chest X-Ray (cxr) images.However, incorporating explainability in these solutions remains relatively less explored...

Dynamic Neural Graphs Based Federated Reptile for Semi-Supervised Multi-Tasking in Healthcare Applications.

IEEE journal of biomedical and health informatics
AI healthcare applications rely on sensitive electronic healthcare records (EHRs) that are scarcely labelled and are often distributed across a network of the symbiont institutions. It is challenging to train the effective machine learning models on ...

AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy.

IEEE journal of biomedical and health informatics
Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment...