AIMC Topic: Humans

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Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review.

The Lancet. Digital health
Adverse drug events (ADEs) represent one of the most prevalent types of health-care-related harm, and there is substantial room for improvement in the way that they are currently predicted and detected. We conducted a scoping review to identify key u...

Calcium Scoring at Coronary CT Angiography Using Deep Learning.

Radiology
Background Separate noncontrast CT to quantify the coronary artery calcium (CAC) score often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA would eliminate the additional radiation produced at CT but remains challengin...

AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data.

Journal of biomedical informatics
BACKGROUND: Scoring systems are highly interpretable and widely used to evaluate time-to-event outcomes in healthcare research. However, existing time-to-event scores are predominantly created ad-hoc using a few manually selected variables based on c...

Concurrently bendable and rotatable continuum tubular robot for omnidirectional multi-core transurethral prostate biopsy.

Medical & biological engineering & computing
A transurethral prostate biopsy device is proposed in this paper, which can shoot a biopsy needle at different angles to take samples from multiple locations within the prostate. Firstly, the traditional prostate biopsy methods, including transrectal...

Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor.

Thoracic cancer
BACKGROUND: Rapid intraoperative diagnosis for unconfirmed pulmonary tumor is extremely important for determining the optimal surgical procedure (lobectomy or sublobar resection). Attempts to diagnose malignant tumors using mass spectrometry (MS) hav...

A blind randomized validated convolutional neural network for auto-segmentation of clinical target volume in rectal cancer patients receiving neoadjuvant radiotherapy.

Cancer medicine
BACKGROUND: Delineation of clinical target volume (CTV) for radiotherapy is a time-consuming and labor-intensive work. This study aims to propose a novel convolutional neural network (CNN)-based model for fast auto-segmentation of CTV. To evaluate it...

Implementation and prospective clinical validation of AI-based planning and shimming techniques in cardiac MRI.

Medical physics
PURPOSE: Cardiovascular magnetic resonance (CMR) is a vital diagnostic tool in the management of cardiovascular diseases. The advent of advanced CMR technologies combined with artificial intelligence (AI) has the potential to simplify imaging, reduce...

Personalized Cell Therapy for Patients with Peripheral Arterial Diseases in the Context of Genetic Alterations: Artificial Intelligence-Based Responder and Non-Responder Prediction.

Cells
Stem/progenitor cell transplantation is a potential novel therapeutic strategy to induce angiogenesis in ischemic tissue, which can prevent major amputation in patients with advanced peripheral artery disease (PAD). Thus, clinicians can use cell ther...

Human Behavior Recognition Model Based on Feature and Classifier Selection.

Sensors (Basel, Switzerland)
With the rapid development of the computer and sensor field, inertial sensor data have been widely used in human activity recognition. At present, most relevant studies divide human activities into basic actions and transitional actions, in which bas...

A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions.

Sensors (Basel, Switzerland)
The human immune system is very complex. Understanding it traditionally required specialized knowledge and expertise along with years of study. However, in recent times, the introduction of technologies such as AIoMT (Artificial Intelligence of Medic...