Accurate detection of lung cancer from Computed Tomography (CT) scans is vital for improving patient survival but remains challenging for deep learning models, which struggle with scale variations of pulmonary nodules and the complex…
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Lung cancer remains the top cause of cancer death, demanding consistent decisions. This clinically oriented review synthesizes computer-aided diagnosis across classical imaging, machine learning, and deep learning, emphasizing bedside-proven advances: multimodal CT/PET–clinical fusion; small-data…
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Professor Peter Johnson, NHS national cancer director (Image provided by NHS England)
Five AI tools that help spot warning signs of bowel cancer earlier have been conditionally recommended by the National Institute for Health…
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Multimodal models have enabled the integration of digital pathology, radiology, clinical information, and omics data to enhance Colorectal cancer (CRC) care. This systematic review critically appraises Multimodal digital pathology techniques applied in CRC, their…
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Careful selection of skin lesions that require expert evaluation is important for early skin cancer detection. Yet challenges include lack of cost-effective asymptomatic screening, geographical inequality in access to specialty dermatology, and long wait…
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Alcohol-related cancer risk calculator launches in New South Wales | MobiHealthNews
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Freenome teams up with Roche for cancer screening tests | MobiHealthNews
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The complexity and variability of high-resolution pathological images present significant challenges in computational pathology. While AI-driven pathology foundation models have advanced the field, they require large-scale datasets, substantial storage, and significant computational resources, as…
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Professor Yang Wei of the Nottingham School of Art & Design. Picture provided by Nottingham Trent University
Researchers are developing a smart textiles bra to help women with intellectual disabilities monitor for breast…
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Colorectal cancer recurrence remains a major challenge after curative resection, and accurate tools for early risk assessment are essential to stratify patients and guide personalized therapeutic planning. We developed MPMRecNet, a dual-stream deep learning…
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