AI Medical Compendium Topic:
Software

Clear Filters Showing 741 to 750 of 3426 articles

Identification of adaptor proteins by incorporating deep learning and PSSM profiles.

Methods (San Diego, Calif.)
Adaptor proteins, also known as signal transduction adaptor proteins, are important proteins in signal transduction pathways, and play a role in connecting signal proteins for signal transduction between cells. Studies have shown that adaptor protein...

Unified machine learning protocol for copolymer structure-property predictions.

STAR protocols
Structure-property relationships are extremely valuable when predicting the properties of polymers. This protocol demonstrates a step-by-step approach, based on multiple machine learning (ML) architectures, which is capable of processing copolymer ty...

Human-level play in the game of by combining language models with strategic reasoning.

Science (New York, N.Y.)
Despite much progress in training artificial intelligence (AI) systems to imitate human language, building agents that use language to communicate intentionally with humans in interactive environments remains a major challenge. We introduce Cicero, t...

Retrospective analysis and prospective validation of an AI-based software for intracranial haemorrhage detection at a high-volume trauma centre.

Scientific reports
Rapid detection of intracranial haemorrhage (ICH) is crucial for assessing patients with neurological symptoms. Prioritising these urgent scans for reporting presents a challenge for radiologists. Artificial intelligence (AI) offers a solution to ena...

Keyword-augmented and semi-automatic generation of FESS reports: a proof-of-concept study.

International journal of computer assisted radiology and surgery
INTRODUCTION: Surgical reports are usually written after a procedure and must often be reproduced from memory. Thus, this is an error-prone, and time-consuming task which increases the workload of physicians. In this proof-of-concept study, we develo...

Robotic Platform for Horticulture: Assessment Methodology and Increasing the Level of Autonomy.

Sensors (Basel, Switzerland)
The relevance of the study is confirmed by the rapid development of automation in agriculture, in particular, horticulture; the lack of methodological developments to assess the effectiveness of the introduction of robotic technologies; and the need ...

Software for segmenting and quantifying calcium signals using multi-scale generative adversarial networks.

STAR protocols
Cellular calcium fluorescence imaging utilized to study cellular behaviors typically results in large datasets and a profound need for standardized and accurate analysis methods. Here, we describe open-source software (4SM) to overcome these limitati...

Deep Learning-Based Segmentation of Cryo-Electron Tomograms.

Journal of visualized experiments : JoVE
Cryo-electron tomography (cryo-ET) allows researchers to image cells in their native, hydrated state at the highest resolution currently possible. The technique has several limitations, however, that make analyzing the data it generates time-intensiv...

Effect of AI-assisted software on inter- and intra-observer variability for the X-ray bone age assessment of preschool children.

BMC pediatrics
BACKGROUND: With the rapid development of deep learning algorithms and the rapid improvement of computer hardware in the past few years, AI-assisted diagnosis software for bone age has achieved good diagnostic performance. The purpose of this study w...

Cellpose 2.0: how to train your own model.

Nature methods
Pretrained neural network models for biological segmentation can provide good out-of-the-box results for many image types. However, such models do not allow users to adapt the segmentation style to their specific needs and can perform suboptimally fo...