AIMC Topic: Deep Learning
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Global Cross-Entropy Loss for Deep Face Recognition.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 11, 2025
Contemporary deep face recognition techniques predominantly utilize the Softmax loss function, designed based on the similarities between sample features and class prototypes. These similarities can be categorized into four types: in-sample target si...
A deep-learning model to predict the completeness of cytoreductive surgery in colorectal cancer with peritoneal metastasis☆.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Mar 10, 2025
BACKGROUND: Colorectal cancer (CRC) with peritoneal metastasis (PM) is associated with poor prognosis. The Peritoneal Cancer Index (PCI) is used to evaluate the extent of PM and to select Cytoreductive Surgery (CRS). However, PCI score is not accurat...
Dual-Modality Virtual Biopsy System Integrating MRI and MG for Noninvasive Predicting HER2 Status in Breast Cancer.
Academic radiology
Mar 10, 2025
RATIONALE AND OBJECTIVES: Accurate determination of human epidermal growth factor receptor 2 (HER2) expression is critical for guiding targeted therapy in breast cancer. This study aimed to develop and validate a deep learning (DL)-based decision-mak...
deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria.
mSystems
Mar 10, 2025
Selenoproteins are a special group of proteins with major roles in cellular antioxidant defense. They contain the 21st amino acid selenocysteine (Sec) in the active sites, which is encoded by an in-frame UGA codon. Compared to eukaryotes, identificat...
Enhancing short-term algal bloom forecasting through an anti-mimicking hybrid deep learning method.
Journal of environmental management
Mar 10, 2025
Accurately predicting algal blooms remains a critical challenge due to their dynamic and non-stationary nature, compounded by high-frequency fluctuations and noise in monitoring data. Additionally, a common issue in time-series forecasting is data re...
Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance.
The international journal of cardiovascular imaging
Mar 10, 2025
Invasive coronary physiology is underused and carries risks/costs. Artificial Intelligence (AI) might enable non-invasive physiology from invasive coronary angiography (CAG), possibly outperforming humans, but has seldom been explored, especially for...
Cancer Drug Sensitivity Prediction Based on Deep Transfer Learning.
International journal of molecular sciences
Mar 10, 2025
In recent years, many approved drugs have been discovered using phenotypic screening, which elaborates the exact mechanisms of action or molecular targets of drugs. Drug susceptibility prediction is an important type of phenotypic screening. Large-sc...
Dementia Overdiagnosis in Younger, Higher Educated Individuals Based on MMSE Alone: Analysis Using Deep Learning Technology.
Journal of Korean medical science
Mar 10, 2025
BACKGROUND: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment,...
A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer: a two-center study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 10, 2025
BACKGROUND: To construct and assess a deep learning (DL) signature that employs computed tomography imaging to predict the expression status of programmed cell death ligand 1 in patients with bladder cancer (BCa).
Development of a deep learning-based model for guiding a dissection during robotic breast surgery.
Breast cancer research : BCR
Mar 10, 2025
BACKGROUND: Traditional surgical education is based on observation and assistance in surgical practice. Recently introduced deep learning (DL) techniques enable the recognition of the surgical view and automatic identification of surgical landmarks. ...
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