AIMC Topic: Humans

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Deep learning-based measurement of echocardiographic data and its application in the diagnosis of sudden cardiac death.

Biotechnology & genetic engineering reviews
This study aimed to evaluate the potential of deep learning applied to the measurement of echocardiographic data in patients with sudden cardiac death (SCD). 320 SCD patients who met the inclusion and exclusion criteria underwent clinical evaluation,...

Modulating autophagy to treat diseases: A revisited review on in silico methods.

Journal of advanced research
BACKGROUND: Autophagy refers to the conserved cellular catabolic process relevant to lysosome activity and plays a vital role in maintaining the dynamic equilibrium of intracellular matter by degrading harmful and abnormally accumulated cellular comp...

From jeopardy champion to drug discovery; semantic similarity artificial intelligence.

Autophagy
We have employed artificial intelligence to streamline the small molecule drug screening pipeline and identified the cholesterol-reducing compound probucol in the process. Probucol augmented mitophagy and prevented loss of dopaminergic neurons in fli...

Robot-assisted stereoencephalography vs subdural electrodes in the evaluation of temporal lobe epilepsy.

Epilepsia open
OBJECTIVE: Invasive video-electroencephalography (iVEEG) is the gold standard for evaluation of refractory temporal lobe epilepsy before second stage resective surgery (SSRS). Traditionally, the presumed seizure onset zone (SOZ) has been covered with...

Pediatrics in Artificial Intelligence Era: A Systematic Review on Challenges, Opportunities, and Explainability.

Indian pediatrics
BACKGROUND: The emergence of artificial intelligence (AI) tools such as ChatGPT and Bard is disrupting a broad swathe of fields, including medicine. In pediatric medicine, AI is also increasingly being used across multiple subspecialties. However, th...

Deep learning PET/CT-based radiomics integrates clinical data: A feasibility study to distinguish between tuberculosis nodules and lung cancer.

Thoracic cancer
BACKGROUND: Radiomic diagnosis models generally consider only a single dimension of information, leading to limitations in their diagnostic accuracy and reliability. The integration of multiple dimensions of information into the deep learning model h...

Optimising trajectory planning for stereotactic brain tumour biopsy using artificial intelligence: a systematic review of the literature.

British journal of neurosurgery
PURPOSE: Despite advances in technology, stereotactic brain tumour biopsy remains challenging due to the risk of injury to critical structures. Indeed, choosing the correct trajectory remains essential to patient safety. Artificial intelligence can b...

A Deep Learning Pipeline Using Prior Knowledge for Automatic Evaluation of Placenta Accreta Spectrum Disorders With MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The diagnosis of prenatal placenta accreta spectrum (PAS) with magnetic resonance imaging (MRI) is highly dependent on radiologists' experience. A deep learning (DL) method using the prior knowledge that PAS-related signs are generally fo...

Deep learning-based reconstruction and 3D hybrid profile order technique for MRCP at 3T: evaluation of image quality and acquisition time.

European radiology
OBJECTIVES: To evaluate the image quality of the 3D hybrid profile order technique and deep-learning-based reconstruction (DLR) for 3D magnetic resonance cholangiopancreatography (MRCP) within a single breath-hold (BH) at 3 T magnetic resonance imagi...