AI Medical Compendium Journal:
STAR protocols

Showing 1 to 10 of 46 articles

Protocol for AI-based segmentation and quantification of interstitial cells of Cajal in murine gastric muscle.

STAR protocols
Interstitial cells of Cajal (ICCs), pacemaker and neuromodulator cells in the gastrointestinal (GI) tract, play an important role in GI motility. However, quantifying ICCs is challenging due to their mixed morphologies. Here, we present a protocol fo...

Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis.

STAR protocols
Here, we present a protocol for the rapid functional screening of gene editing and addition strategies in patient-derived organoids using the deep-learning-based tool DETECTOR (detection of targeted editing of cystic fibrosis transmembrane conductanc...

Protocol to infer off-target effects of drugs on cellular signaling using interactome-based deep learning.

STAR protocols
Drugs that target specific proteins often have off-target effects. We present a protocol using artificial neural networks to model cellular transcriptional responses to drugs, aiming to understand their mechanisms of action. We detail steps for predi...

Protocol for artificial intelligence-guided neural control using deep reinforcement learning and infrared neural stimulation.

STAR protocols
Closed-loop neural control is a powerful tool for both the scientific exploration of neural function and for mitigating deficiencies found in open-loop deep brain stimulation (DBS). Here, we present a protocol for artificial intelligence-guided neura...

Protocol to calculate and compare exact Shapley values for different kernels in support vector machine models using binary features.

STAR protocols
The Shapley value formalism from cooperative game theory was adapted to explain predictions of machine learning models. Here, we present a protocol to calculate and compare exact Shapley values for support vector machine models with commonly used ker...

Protocol for UAV fault diagnosis using signal processing and machine learning.

STAR protocols
Unmanned aerial vehicles (UAVs) require fault diagnosis for safe operation. Here, we present a protocol for UAV fault diagnosis using signal processing and artificial intelligence. We describe steps for collecting vibration-based signal data, preproc...

Protocol for developing an explosion-propeller hybrid driving underwater robot for AI-based concrete overhaul in real marine environments.

STAR protocols
We recently developed an explosion-propeller hybrid driving underwater robot combined with an AI-based concrete damage detection technique for concrete overhaul in real marine environments. Here, we describe steps for establishing a detection dataset...

Protocol for machine-learning-based 3D image analysis of nuclear envelope tubules in cultured cells.

STAR protocols
The nuclear envelope can form complex structures in physiological and pathological contexts. Current approaches to quantify nuclear envelope structures can be time-consuming or inaccurate. Here, we present a protocol to measure nuclear envelope tubul...

Protocol for performing deep learning-based fundus fluorescein angiography image analysis with classification and segmentation tasks.

STAR protocols
Fundus fluorescein angiography (FFA) examinations are widely used in the evaluation of fundus disease conditions to facilitate further treatment suggestions. Here, we present a protocol for performing deep learning-based FFA image analytics with clas...

A deep learning framework for denoising and ordering scRNA-seq data using adversarial autoencoder with dynamic batching.

STAR protocols
Single-cell RNA sequencing (scRNA-seq) provides high resolution of cell-to-cell variation in gene expression and offers insights into cell heterogeneity, differentiating dynamics, and disease mechanisms. However, technical challenges such as low capt...