AIMC Topic: Humans

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Minimizing and quantifying uncertainty in AI-informed decisions: Applications in medicine.

Proceedings of the National Academy of Sciences of the United States of America
AI is now a cornerstone of modern dataset analysis. In many real world applications, practitioners are concerned with controlling specific kinds of errors, rather than minimizing the overall number of errors. For example, biomedical screening assays ...

Efficiently quantifying dependence in massive scientific datasets using InterDependence Scores.

Proceedings of the National Academy of Sciences of the United States of America
Large-scale scientific datasets today contain tens of thousands of random variables across millions of samples (for example, the RNA expression levels of 20,000 protein-coding genes across 30 million single cells). Being able to quantify dependencies...

Artificial Intelligence in Healthcare: Current Regulatory Landscape and Future Directions.

British journal of hospital medicine (London, England : 2005)
The integration of artificial intelligence (AI) in healthcare offers the potential to play a critical role in reshaping clinical practice. However, it also brings regulatory, ethical, implementation, social, and technical challenges that healthcare s...

External validation of precisebreast, a digital prognostic test for predicting breast cancer recurrence, in an early-stage cohort from the Netherlands.

Breast cancer research : BCR
BACKGROUND: Current clinical guidelines recommend gene expression profiling to guide treatment in early-stage breast cancer. PreciseBreast (PDxBR) is a digital prognostic tool that integrates artificial intelligence (AI)-derived features from hematox...

Criteria-calibration approaches to deep learning-based cervical cancer radiation treatment auto-planning.

Radiation oncology (London, England)
BACKGROUND: Knowledge-Based Planning (KBP) pipelines, which integrate machine learning-based models to predict dose distribution, have gained popularity in clinical radiation therapy. However, for patients with specific requirements, the trained mode...

AI-assisted 3D versus conventional 2D preoperative planning in total hip arthroplasty for Crowe type II-IV high hip dislocation: a two-year retrospective study.

Journal of orthopaedic surgery and research
BACKGROUND: With the growing complexity of total hip arthroplasty (THA) for high hip dislocation (HHD), artificial intelligence (AI)-assisted three-dimensional (3D) preoperative planning has emerged as a promising tool to enhance surgical accuracy. T...

Machine learning-assisted radiogenomic analysis for miR-15a expression prediction in renal cell carcinoma.

BMC cancer
BACKGROUND: Renal cell carcinoma (RCC) is a prevalent malignancy with highly variable outcomes. MicroRNA-15a (miR-15a) has emerged as a promising prognostic biomarker in RCC, linked to angiogenesis, apoptosis, and proliferation. Radiogenomics integra...

Automatic detection of cognitive events using machine learning and understanding models' interpretations of human cognition.

Scientific reports
The pupillary response is a valuable indicator of cognitive workload, capturing fluctuations in attention and arousal governed by the autonomic nervous system. Cognitive events, defined as the initiation of mental processes, are closely linked to cog...

Evaluating forecasting models for health service demand during the COVID-19 pandemic.

Scientific reports
We combine daily internet search data and monthly information on medical expenditures for anti-depressants to test two distinct hypotheses in eight Australian states, covering the period from 2020 to 2022. First, whether using daily search data can h...

A smart secure virtual reality immersive application for alzheimer's and dementia patients.

Scientific reports
Alzheimer's disease (AD) poses significant challenges for the elderly, leading to cognitive decline, social isolation, and lower quality of life. Current interventions often require cumbersome wearable devices e.g. the camera-based monitoring that ma...