AIMC Topic: Algorithms

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Deep multi-task learning framework for gastrointestinal lesion-aided diagnosis and severity estimation.

Scientific reports
Accurate diagnosis and severity estimation of gastrointestinal tract (GT) lesions are crucial for patient care and effective treatment plan decisions. Traditional methods for diagnosing lesions face challenges in accurately estimating severity due to...

New hybrid features extracted from US images for breast cancer classification.

Scientific reports
Artificial intelligence (AI), and image processing fields play a vital role in classifying benign and malignant breast cancer (BC). The novelty of this paper lies in computing original hybrid features (HF) from textural and shape features of BC integ...

Enhancing pathological feature discrimination in diabetic retinopathy multi-classification with self-paced progressive multi-scale training.

Scientific reports
Diabetic retinopathy (DR) is a common diabetes complication that presents significant diagnostic challenges due to its reliance on expert assessment and the subtlety of small lesions. Although deep learning has shown promise, its effectiveness is oft...

Optimization of a multi-environmental detection model for tomato growth point buds based on multi-strategy improved YOLOv8.

Scientific reports
Tomato growing points and flower buds serve as vital physiological indicators influencing yield quality, yet their detection remains challenging in complex facility environments. This study develops an improved YOLOv8 model for robust flower bud dete...

Surgical embodied intelligence for generalized task autonomy in laparoscopic robot-assisted surgery.

Science robotics
Surgical robots capable of autonomously performing various tasks could enhance efficiency and augment human productivity in addressing clinical needs. Although current solutions have automated specific actions within defined contexts, they are challe...

Automated multi-model framework for malaria detection using deep learning and feature fusion.

Scientific reports
Malaria remains a critical global health challenge, particularly in tropical and subtropical regions. While traditional methods for diagnosis are effective, they face some limitations related to accuracy, time consumption, and manual effort. This stu...

An explainable and federated deep learning framework for skin cancer diagnosis.

PloS one
Skin cancer (SC) is the most prominent form of cancer in humans, with over 1 million new cases reported worldwide each year. Early identification of SC plays a crucial role in effective treatment. However, protecting patient data privacy is a major c...

Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models.

PloS one
Electronic payment methods are increasingly prevalent worldwide, facilitating both in-person and online transactions. As credit card usage for online payments grows, fraud and payment defaults have also risen, resulting in significant financial losse...

Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.

PloS one
BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammatory responses from infections. It poses significant challenges in clinical management and is associated with poor outcomes. Survivors often...

Mapping burnt areas using very high-resolution imagery and deep learning algorithms - a case study in Bandipur, India.

PloS one
Burnt area (BA) mapping is crucial for assessing wildfire impact, guiding restoration efforts, and improving fire management strategies. Accurate BA data helps estimate carbon emissions, biodiversity loss, and land surface properties post-fire change...