AIMC Topic: Pancreas

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[Robotic pancreatic surgery].

Chirurgie (Heidelberg, Germany)
Robotic operations as a further development of conventional laparoscopic surgery have been introduced for nearly all interventions in visceral surgery during the last decade. They also currently have a high importance and acceptance in pancreatic sur...

Artificial intelligence assisted endoscopic ultrasound for detection of pancreatic space-occupying lesion: a systematic review and meta-analysis.

International journal of surgery (London, England)
BACKGROUND: Diagnosing pancreatic lesions, including chronic pancreatitis, autoimmune pancreatitis, and pancreatic cancer, poses a challenge and, as a result, is time-consuming. To tackle this issue, artificial intelligence (AI) has been increasingly...

Large-scale pancreatic cancer detection via non-contrast CT and deep learning.

Nature medicine
Pancreatic ductal adenocarcinoma (PDAC), the most deadly solid malignancy, is typically detected late and at an inoperable stage. Early or incidental detection is associated with prolonged survival, but screening asymptomatic individuals for PDAC usi...

[Current CT developments in imaging of pancreatic diseases].

Radiologie (Heidelberg, Germany)
BACKGROUND: Diseases of the pancreas are often diagnosed late and can have fatal consequences for patients.

CT scan pancreatic cancer segmentation and classification using deep learning and the tunicate swarm algorithm.

PloS one
Pancreatic cancer (PC) is a very lethal disease with a low survival rate, making timely and accurate diagnoses critical for successful treatment. PC classification in computed tomography (CT) scans is a vital task that aims to accurately discriminate...

A deep learning model to triage and predict adenocarcinoma on pancreas cytology whole slide imaging.

Scientific reports
Pancreatic fine-needle aspirations are the gold-standard diagnostic procedure for the evaluation of pancreatic ductal adenocarcinoma. A suspicion for malignancy can escalate towards chemotherapy followed by a major surgery and therefore is a high-sta...

Identifying the serious clinical outcomes of adverse reactions to drugs by a multi-task deep learning framework.

Communications biology
Adverse Drug Reactions (ADRs) have a direct impact on human health. As continuous pharmacovigilance and drug monitoring prove to be costly and time-consuming, computational methods have emerged as promising alternatives. However, most existing comput...

Hybrid AI models allow label-free identification and classification of pancreatic tumor repopulating cell population.

Biochemical and biophysical research communications
Human pancreatic cancer cell lines harbor a small population of tumor repopulating cells (TRCs). Soft 3D fibrin gel allows efficient selection and growth of these tumorigenic TRCs. However, rapid and high-throughput identification and classification ...

MISPEL: A supervised deep learning harmonization method for multi-scanner neuroimaging data.

Medical image analysis
Large-scale data obtained from aggregation of already collected multi-site neuroimaging datasets has brought benefits such as higher statistical power, reliability, and robustness to the studies. Despite these promises from growth in sample size, sub...

A review of deep learning and radiomics approaches for pancreatic cancer diagnosis from medical imaging.

Current opinion in gastroenterology
PURPOSE OF REVIEW: Early and accurate diagnosis of pancreatic cancer is crucial for improving patient outcomes, and artificial intelligence (AI) algorithms have the potential to play a vital role in computer-aided diagnosis of pancreatic cancer. In t...