AIMC Topic: Humans

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Neural patient-specific 3D-2D registration in laparoscopic liver resection.

International journal of computer assisted radiology and surgery
PURPOSE: Augmented reality guidance in laparoscopic liver resection requires the registration of a preoperative 3D model to the intraoperative 2D image. However, 3D-2D liver registration poses challenges owing to the liver's flexibility, particularly...

Transforming Hypertension Diagnosis and Management in The Era of Artificial Intelligence: A 2023 National Heart, Lung, and Blood Institute (NHLBI) Workshop Report.

Hypertension (Dallas, Tex. : 1979)
Hypertension is among the most important risk factors for cardiovascular disease, chronic kidney disease, and dementia. The artificial intelligence (AI) field is advancing quickly, and there has been little discussion on how AI could be leveraged for...

Brief Review and Primer of Key Terminology for Artificial Intelligence and Machine Learning in Hypertension.

Hypertension (Dallas, Tex. : 1979)
Recent breakthroughs in artificial intelligence (AI) have caught the attention of many fields, including health care. The vision for AI is that a computer model can process information and provide output that is indistinguishable from that of a human...

A depth analysis of recent innovations in non-invasive techniques using artificial intelligence approach for cancer prediction.

Medical & biological engineering & computing
The fight against cancer, a relentless global health crisis, emphasizes the urgency for efficient and automated early detection methods. To address this critical need, this review assesses recent advances in non-invasive cancer prediction techniques,...

Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution.

Neural networks : the official journal of the International Neural Network Society
Traffic flow prediction is crucial for efficient traffic management. It involves predicting vehicle movement patterns to reduce congestion and enhance traffic flow. However, the highly non-linear and complex patterns commonly observed in traffic flow...

Evaluation of Artificial Intelligence-Based Gleason Grading Algorithms "in the Wild".

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
The biopsy Gleason score is an important prognostic marker for prostate cancer patients. It is, however, subject to substantial variability among pathologists. Artificial intelligence (AI)-based algorithms employing deep learning have shown their abi...

Robot-related injuries in the workplace: An analysis of OSHA Severe Injury Reports.

Applied ergonomics
Industrial robots are increasingly commonplace, but research on prototypical accidents and injuries has been sparse, hindering evidence-based safety strategies. Using Severe Injury Reports (SIRs) from the U.S. Occupational Safety and Health Administr...

Cognitive and behavioral markers for human detection error in AI-assisted bridge inspection.

Applied ergonomics
Integrating Artificial Intelligence (AI) and drone technology into bridge inspections offers numerous advantages, including increased efficiency and enhanced safety. However, it is essential to recognize that this integration changes the cognitive er...

Optimized multi-head self-attention and gated-dilated convolutional neural network for quantum key distribution and error rate reduction.

Network (Bristol, England)
Quantum key distribution (QKD) is a secure communication method that enables two parties to securely exchange a secret key. The secure key rate is a crucial metric for assessing the efficiency and practical viability of a QKD system. There are severa...

Machine Learning for Early Discrimination Between Lung Cancer and Benign Nodules Using Routine Clinical and Laboratory Data.

Annals of surgical oncology
BACKGROUND: Lung cancer poses a global health threat necessitating early detection and precise staging for improved patient outcomes. This study focuses on developing and validating a machine learning-based risk model for early lung cancer screening ...