AIMC Topic: Artificial Intelligence

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Advances in artificial intelligence to predict cancer immunotherapy efficacy.

Frontiers in immunology
Tumor immunotherapy, particularly the use of immune checkpoint inhibitors, has yielded impressive clinical benefits. Therefore, it is critical to accurately screen individuals for immunotherapy sensitivity and forecast its efficacy. With the applicat...

Artificial intelligence and machine learning approaches in composting process: A review.

Bioresource technology
Studies on developing strategies to predict the stability and performance of the composting process have increased in recent years. Machine learning (ML) has focused on process optimization, prediction of missing data, detection of non-conformities, ...

Perspectives for self-driving labs in synthetic biology.

Current opinion in biotechnology
Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is pr...

Development and Validation of a Deep Learning Algorithm to Differentiate Colon Carcinoma From Acute Diverticulitis in Computed Tomography Images.

JAMA network open
IMPORTANCE: Differentiating between malignant and benign etiology in large-bowel wall thickening on computed tomography (CT) images can be a challenging task. Artificial intelligence (AI) support systems can improve the diagnostic accuracy of radiolo...

Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment.

Sensors (Basel, Switzerland)
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolutio...

A Self-Collision Detection Algorithm of a Dual-Manipulator System Based on GJK and Deep Learning.

Sensors (Basel, Switzerland)
Self-collision detection is fundamental to the safe operation of multi-manipulator systems, especially when cooperating in highly dynamic working environments. Existing methods still face the problem that detection efficiency and accuracy cannot be a...

Development of a Machine Learning Model for Sonographic Assessment of Gestational Age.

JAMA network open
IMPORTANCE: Fetal ultrasonography is essential for confirmation of gestational age (GA), and accurate GA assessment is important for providing appropriate care throughout pregnancy and for identifying complications, including fetal growth disorders. ...

Clustering of critically ill patients using an individualized learning approach enables dose optimization of mobilization in the ICU.

Critical care (London, England)
BACKGROUND: While early mobilization is commonly implemented in intensive care unit treatment guidelines to improve functional outcome, the characterization of the optimal individual dosage (frequency, level or duration) remains unclear. The aim of t...

Surgeons' perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey.

World journal of emergency surgery : WJES
BACKGROUND: Artificial intelligence (AI) is gaining traction in medicine and surgery. AI-based applications can offer tools to examine high-volume data to inform predictive analytics that supports complex decision-making processes. Time-sensitive tra...

Image dataset for benchmarking automated fish detection and classification algorithms.

Scientific data
Multiparametric video-cabled marine observatories are becoming strategic to monitor remotely and in real-time the marine ecosystem. Those platforms can achieve continuous, high-frequency and long-lasting image data sets that require automation in ord...