AIMC Topic: Humans

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Ambulatory robot-assisted laparoscopic radical prostatectomy with extended recovery by total extraperitoneal approach.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVE: To evaluate the feasibility of performing robot-assisted laparoscopic radical prostatectomy in an ambulatory with extended recovery setting by using a total extraperitoneal approach.

A stochastic numerical analysis based on hybrid NAR-RBFs networks nonlinear SITR model for novel COVID-19 dynamics.

Computer methods and programs in biomedicine
BACKGROUND: Mathematical modeling of vector-borne diseases and forecasting of epidemics outbreak are global challenges and big point of concern worldwide. The outbreaks depend on different social and demographic factors based on human mobility struct...

BloodCaps: A capsule network based model for the multiclassification of human peripheral blood cells.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The classification of human peripheral blood cells yields significance in the detection of inflammation, infections and blood cell disorders such as leukemia. Limitations in traditional algorithms for blood cell classificati...

Advances in de Novo Drug Design: From Conventional to Machine Learning Methods.

International journal of molecular sciences
. De novo drug design is a computational approach that generates novel molecular structures from atomic building blocks with no a priori relationships. Conventional methods include structure-based and ligand-based design, which depend on the properti...

Use of Artificial Intelligence in the Prediction of Malignant Potential of Gastric Gastrointestinal Stromal Tumors.

Digestive diseases and sciences
BACKGROUND AND AIMS: This study aimed to investigate whether AI via a deep learning algorithm using endoscopic ultrasonography (EUS) images could predict the malignant potential of gastric gastrointestinal stromal tumors (GISTs).

Imaging-Based Outcome Prediction of Acute Intracerebral Hemorrhage.

Translational stroke research
We hypothesized that imaging-only-based machine learning algorithms can analyze non-enhanced CT scans of patients with acute intracerebral hemorrhage (ICH). This retrospective multicenter cohort study analyzed 520 non-enhanced CT scans and clinical d...

Lung Cancer and Granuloma Identification Using a Deep Learning Model to Extract 3-Dimensional Radiomics Features in CT Imaging.

Clinical lung cancer
BACKGROUND: We aimed to evaluate a deep learning (DL) model combining perinodular and intranodular radiomics features and clinical features for preoperative differentiation of solitary granuloma nodules (GNs) from solid lung cancer nodules in patient...

Attention Guided Lymph Node Malignancy Prediction in Head and Neck Cancer.

International journal of radiation oncology, biology, physics
PURPOSE: Accurate lymph node (LN) malignancy classification is essential for treatment target identification in head and neck cancer (HNC) radiation therapy. Given the constraints imposed by relatively small sample sizes in real-world medical applica...