AIMC Topic: Humans

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A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey.

Journal of imaging informatics in medicine
In recent years, the role of Artificial Intelligence (AI) in medical imaging has become increasingly prominent, with the majority of AI applications approved by the FDA being in imaging and radiology in 2023. The surge in AI model development to tack...

Electro-Thermopneumatically Actuated, Adhesion-Force Controllable Octopus-Like Suction Cup Actuator.

Soft robotics
A light-weight actuator developed in this work belongs to a class of soft robots, and in a sense, resembles an octopus. Its main function is in the attachment or detachment to a solid surface driven by an electro-thermopneumatic mechanism. In this st...

Simplified detection of genetic background admixture using artificial intelligence.

Clinical genetics
Admixture refers to the mixing of genetic ancestry from different populations. Admixture is important for genomic medicine because it can affect how an individual responds to certain medications, how they metabolize drugs, and susceptibility to certa...

Creating a Bot-tleneck for malicious AI: Psychological methods for bot detection.

Behavior research methods
The standard approach for detecting and preventing bots from doing harm online involves CAPTCHAs. However, recent AI research, including our own in this manuscript, suggests that bots can complete many common CAPTCHAs with ease. The most effective me...

Unmasking the sky: high-resolution PM prediction in Texas using machine learning techniques.

Journal of exposure science & environmental epidemiology
BACKGROUND: Although PM (fine particulate matter with an aerodynamic diameter less than 2.5 µm) is an air pollutant of great concern in Texas, limited regulatory monitors pose a significant challenge for decision-making and environmental studies.

Electrocardiography-based Artificial Intelligence Algorithms Aid in Prediction of Long-term Mortality After Kidney Transplantation.

Transplantation
BACKGROUND: Predicting long-term mortality postkidney transplantation (KT) using baseline clinical data presents significant challenges. This study aims to evaluate the predictive power of artificial intelligence (AI)-enabled analysis of preoperative...

Current applications of artificial intelligence in assisted reproductive technologies through the perspective of a patient's journey.

Current opinion in obstetrics & gynecology
PURPOSE OF REVIEW: This review highlights the timely relevance of artificial intelligence in enhancing assisted reproductive technologies (ARTs), particularly in-vitro fertilization (IVF). It underscores artificial intelligence's potential in revolut...

Concerns with OpenAI's Sora in Medicine.

Annals of biomedical engineering
Open AI's Sora represents a ground-breaking innovation in AI that can generate lifelike and imaginative visual scenes based on text prompts. However, Sora has also produced some new concerns surrounding artificial video generation in medicine. While ...

Generalizability of machine learning models predicting 30-day unplanned readmission after primary total knee arthroplasty using a nationally representative database.

Medical & biological engineering & computing
Unplanned readmission after primary total knee arthroplasty (TKA) costs an average of US $39,000 per episode and negatively impacts patient outcomes. Although predictive machine learning (ML) models show promise for risk stratification in specific po...

Identifying gray matter alterations in Cushing's disease using machine learning: An interpretable approach.

Medical physics
BACKGROUND: Cushing's Disease (CD) is a rare clinical syndrome characterized by excessive secretion of adrenocorticotrophic hormone, leading to significant functional and structural brain alterations as observed in Magnetic Resonance Imaging (MRI). W...