AIMC Topic: Humans

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Machine Learning-Assisted Preoperative Diagnosis of Infection Stones in Urolithiasis Patients.

Journal of endourology
The decision-making of how to treat urinary infection stones was complicated by the difficulty in preoperative diagnosis of these stones. Hence, we developed machine learning (ML) models that can be leveraged to discriminate between infection and no...

Deciphering the blackbox of omics approaches and artificial intelligence in food waste transformation and mitigation.

International journal of food microbiology
It is necessary to stop the wastage of food during any stage of food chain to resolve the challenge of starvation, hunger and malnutrition in the world. Inception of modern techniques like omics (metagenomics, proteomics, transcriptomics, wasteomics,...

Detection of schizophrenia using hybrid of deep learning and brain effective connectivity image from electroencephalogram signal.

Computers in biology and medicine
Detection of mental disorders such as schizophrenia (SZ) through investigating brain activities recorded via Electroencephalogram (EEG) signals is a promising field in neuroscience. This study presents a hybrid brain effective connectivity and deep l...

POTTER-ICU: An artificial intelligence smartphone-accessible tool to predict the need for intensive care after emergency surgery.

Surgery
BACKGROUND: Delays in admitting high-risk emergency surgery patients to the intensive care unit result in worse outcomes and increased health care costs. We aimed to use interpretable artificial intelligence technology to create a preoperative predic...

Short-term results of robot-assisted colorectal cancer surgery using Senhance Digital Laparoscopy System.

Asian journal of endoscopic surgery
BACKGROUND: The Senhance Digital Laparoscopy System (Asensus Surgical Inc, Morrisville, NC, United States), which was introduced for the first time in Japan by our hospital, is a new surgical assistive robot following the da Vinci Surgical System. We...

Spatial analysis of tumor-infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma.

The journal of pathology. Clinical research
This study aimed to explore the prognostic impact of spatial distribution of tumor-infiltrating lymphocytes (TILs) quantified by deep learning (DL) approaches based on digitalized whole-slide images stained with hematoxylin and eosin in patients with...

Labeling Noncontrast Head CT Reports for Common Findings Using Natural Language Processing.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Prioritizing reading of noncontrast head CT examinations through an automated triage system may improve time to care for patients with acute neuroradiologic findings. We present a natural language-processing approach for label...

[Modern mid-field magnetic resonance imaging in private practice : Field report].

Der Radiologe
BACKGROUND: With the 0.55 T magnetic resonance imaging (MRI) scanner "Free.Max", a new device concept in the mid-field sector is being introduced into the market. New technologies and artificial intelligence (AI) applications as well as a new coil co...

Deep learning from multiple experts improves identification of amyloid neuropathologies.

Acta neuropathologica communications
Pathologists can label pathologies differently, making it challenging to yield consistent assessments in the absence of one ground truth. To address this problem, we present a deep learning (DL) approach that draws on a cohort of experts, weighs each...