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Healthcare Technology Letters
Scopus
ISSN 2053-3713 · Wiley · 337 artikel di indeks
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Artikel Jurnal
Generalized Few‐Shot MM‐Former For Surgical Scene Panoptic Segmentation
ABSTRACT Panoptic segmentation is crucial for surgical scene understanding but remains a significant challenge. This is particularly due to the high cost of annotation, which often results in class imbalance in existing datasets, leading to poor performance on categories with limited samples. To…
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Artikel Jurnal
Deep Learning‐Based Analysis of Mammographic Images for Breast Cancer Detection Using Transfer Learning
ABSTRACT Breast cancer ranks as one of the most perilous diseases, being the second most prevalent disease among women globally. This condition involves a rapid and uncontrolled proliferation of breast cells. Prominent symptoms of breast cancer include alterations in breast size and shape…
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Artikel Jurnal
PRISM: Past‐Regularized Iterative Self‐Distillation With Momentum for Polyp Segmentation
ABSTRACT Polyps are abnormal tissue growths in the colon that may develop into colorectal cancer if left undetected. Accurate segmentation in medical imaging is essential for early diagnosis and treatment. Although deep learning has greatly improved polyp segmentation, its dependence on large…
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Artikel Jurnal
Trustworthy AI in Telehealth: Navigating Challenges, Ethical Considerations, and Future Opportunities for Equitable Healthcare Delivery
ABSTRACT Trustworthy artificial intelligence (TAI) will transform telehealth by providing safe, transparent, and ethically compliant systems that enhance clinician decision‐making and patient relationships. This systematic review examines how TAI and large language models (LLMs), including large…
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Artikel Jurnal
Ensemble Machine Learning Approaches for Automated Fungal Keratitis Diagnosis Using In Vivo Confocal Microscopy Images
ABSTRACT Fungal keratitis (FK) is a severe ocular infection that can lead to significant vision problems or blindness if not diagnosed and treated promptly. Early and accurate detection of FK is essential for effective management. Traditional diagnostic methods are often time‐consuming and require…
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Artikel Jurnal
Real‐Time Tool Detection in Laparoscopic Datasets for Surgical Training in Low‐Resource Settings
ABSTRACT In low‐resource settings, there is a critical need for skilled surgeons. Alternative training processes that include computer‐assisted surgical skill evaluation are essential to address this gap. Using tool detection, surgical videos can be leveraged to derive insights into surgical skill…
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Artikel Jurnal
Improving SLAM‐Based Navigation in Flexible Ureteroscopy by Kidney Stone and Surgical Tool Segmentation
ABSTRACT Flexible ureteroscopy is a widely used surgical procedure for diagnosing and treating various urinary tract conditions, particularly kidney stones. Ensuring the complete extraction of all stones is crucial to prevent recurrence and the need for auxiliary interventions. Visual SLAM‐based…
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Artikel Jurnal
A Self‐Monitoring Mobile App to Mitigate Risk Factors for Suicide and Self‐Harm in Junior (Resident) Doctors: A Review, Thematic Analysis and Concept Proposal
ABSTRACT Doctors, particularly those in training in the UK, are exposed to high levels of stress in their work, which can lead to burnout and mental health problems. According to the health and safety executive (HSE) Management UK standards, employers should recognise and minimise work‐related…
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Markerless Tracking of Robotic Surgical Instruments With Head Mounted Display for Augmented Reality Applications
ABSTRACT In robotic‐assisted laparoscopic surgery, an assistant surgeon stands at the bedside assisting the intervention, while the surgeon sits at the console teleoperating the robot. Tasks for the assistant include navigating new instruments into the surgeon's field‐of‐view and passing in or…
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Artikel Jurnal
A Systematic Review of Artificial Intelligence‐Based Clinical Decision Support Systems in Prostate Cancer Management
ABSTRACT Background Prostate cancer (PCa) affects over 1.4 million individuals annually and remains one of the leading causes of cancer‐related death globally. Artificial intelligence‐based clinical decision support systems (AI‐CDSS) are increasingly used to improve diagnostic and treatment…
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Artikel Jurnal
Artificial Intelligence Challenges in the Healthcare Industry: A Systematic Review of Recent Evidence
ABSTRACT While AI is essential to the development of electronic health, it has challenges that, if resolved, might improve the standard of healthcare services. The purpose of this study is to classify and identify these issues in the healthcare field. The study utilised a systematic review…
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An Analysis of Monitoring Solutions for CAR T Cell Production
ABSTRACT The chimeric antigen receptor T cell (CAR T) therapy has shown remarkable results in treating certain cancers. It involves genetically modifying a patient's T cells to recognize and attack cancer cells. Despite its potential, CAR T cell therapy is complex and costly and requires the…
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Artikel Jurnal
Augmented Reality in Outpatient Care: A Narrative Review
ABSTRACT Introduction Augmented reality (AR) is seeing an increase in its applications in healthcare, but its reach in outpatient care remains undefined. Patients in outpatient settings face poor medical understanding. AR may help address this gap between patients and physicians through immersive…
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Planning Non‐Linear Trajectories for No‐Touch Thermal Ablation Using Passive Steerable Needle With Controlled Stiffness and PSAM
ABSTRACT Percutaneous thermal ablation using a passive steering needle has the potential to help reduce procedure risks and enable multiple ablations with a single insertion. However, manual planning of such procedures is challenging, time‐consuming, and typically done using CT‐scans or tools…
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Artikel Jurnal
Knowledge distillation approach for skin cancer classification on lightweight deep learning model
Abstract Over the past decade, there has been a global increase in the incidence of skin cancers. Skin cancer has serious consequences if left untreated, potentially leading to more advanced cancer stages. In recent years, deep learning based convolutional neural network have emerged as powerful…
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Artikel Jurnal
System for assistance in ultrasound‐guided percutaneous hepatic interventions using augmented reality: First steps
Abstract This study aims to develop a system based on mixed reality imaging for assistance in percutaneous ultrasound‐guided liver interventions. A liver phantom, an ultrasound scanner with an abdominal probe, an electromagnetic tracking system for localization of the ultrasound probe, and the…
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Artikel Jurnal
Monocular Vision‐Based Endoscopic Sinus Navigation: A SLAM Driven Approach With CT Integration
ABSTRACT Surgical navigation is critical in sinus surgery to enhance the surgeon's spatial awareness and improve precision, particularly around occluded critical structures. While external tracker‐based navigation systems exist, vision‐based solutions are preferred for being less intrusive and for…
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Artikel Jurnal
SAMmorph: A Weakly‐Supervised Multimodal Medical Image Registration With SAM‐Based Segmentation and Bidirectional Mechanism
ABSTRACT In this paper, we introduce SAMmorph, a novel multimodal medical image registration framework addressing challenges in aligning cross‐modality images due to significant appearance differences and heavy reliance on expensive annotations. It comprises three key components: the VoxelSAM…
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Artikel Jurnal
Deep regression 2D‐3D ultrasound registration for liver motion correction in focal tumour thermal ablation
Abstract Liver tumour ablation procedures require accurate placement of the needle applicator at the tumour centroid. The lower‐cost and real‐time nature of ultrasound (US) has advantages over computed tomography for applicator guidance, however, in some patients, liver tumours may be occult on US…
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Artikel Jurnal
Automated Detection of Bone Fractures in Muscle X‐Ray Images Using Multiband‐Frequency Aware Deep Representation Learning
ABSTRACT The automated detection of bone fractures in muscle X‐ray (MXR) images using artificial intelligence is vital for successful treatment and better patient outcomes. This paper proposes the multiband‐frequency aware deep representation learning network (MFADRLN)‐based automated approach for…