What You Should Know:
– Lunit, a provider of AI for cancer diagnostics and therapeutics announced a strategic collaboration with Microsoft to accelerate the delivery of AI-powered healthcare solutions globally.
– The partnership, coupled with Lunit’s…
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What You Should Know:
– HOPPR, the company revolutionizing how AI imaging applications are built, validated, and deployed secures $31.5M in an oversubscribed Series A funding round led by Kivu and Greycroft, with participation from…
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Infantile epileptic spasm syndrome (IESS) is a severe neurological disorder characterized by epileptic spasms (ES). Timely diagnosis is crucial, but it is often delayed due to symptom misidentification. Smartphone videos can aid in diagnosis,…
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The Segment Anything Model (SAM) was fine-tuned on the EchoNet-Dynamic dataset and evaluated on external transthoracic echocardiography (TTE) and Point-of-Care Ultrasound (POCUS) datasets from CAMUS (University Hospital of St Etienne) and Mayo Clinic (99…
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News
Ambience Healthcare develops an AI medical coding model using OpenAI’s Reinforcement Fine-Tuning technology that can record and document clinical conversations, and identify and integrate relevant ICD-10 codes for more accurate billing. The company claims…
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The assessment of corneal fluorescein staining is essential, yet current AI models for Corneal Staining Score (CSS) assessments inadequately identify punctate lesions due to annotation challenges and noise, risk misrepresenting treatment responses through “plateau”…
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Google announced the launch of MedGemma, which the company says contains the most capable open models that help developers build healthcare-based AI applications to examine medical images, generate medical image reports, triage patients or…
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Large-language models (LLMs) show promise for clinical note information extraction, but deployment challenges include high computational costs and privacy concerns. We used synthetic data distillation to fine-tune smaller, open-source LLMs to achieve performance comparable…
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Critical findings in radiology reports are life threatening conditions that need to be communicated promptly to physicians for timely management of patients. Although challenging, advancements in natural language processing (NLP), particularly large language models…
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Large language models generate plausible text responses to medical questions, but inaccurate responses pose significant risks in medical decision-making. Grading LLM outputs to determine the best model or answer is time-consuming and impractical in…
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