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Natural Language Processing (NLP) in Spotlight at HIMSS 2023

Imaging Technology

The Boston, MA-based company has announced multiple sessions to demonstrate its industry-leading Clinical Natural Language Understanding (cNLU) technology at HIMSS 2023. They will detail how TVH captures patient attributes from their structured EMR data and unstructured medical notes at scale.

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Penn Medicine to Present Multiple Clinical Trial Results at 2024 ASCO Annual Meeting

Imaging Technology

Schuchter, MD, FASCO , the Madlyn and Leonard Abramson Professor of Clinical Oncology and director of the Tara Miller Melanoma Center at Penn Medicine , is the 2023-2024 ASCO President, and the ASCO Annual Meeting program features more than 200 sessions complementing her Presidential Theme: "The Art and Science of Cancer Care: From Comfort to Cure."

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New Non-Acute Care Roadmap: HIMSS Digital Maturity Model Strategy

Imaging Technology

milla1cf Tue, 04/11/2023 - 21:23 April 11, 2023 — To meet the needs of non-acute healthcare, a global health advocate is launching a newly modernized digital maturity model. It focuses on wellness, illness prevention, and the use of technology to help manage chronic disease at home and keeping patients out of the hospital.

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C-COMM: HIMSS New Non-Acute Care Digital Maturity Model

Imaging Technology

milla1cf Fri, 04/21/2023 - 22:45 April 21, 2023 — To meet the needs of non-acute healthcare, HIMSS is launching a newly modernized digital maturity model, Community Care Outcomes Maturity Model (C-COMM). For more information: www.himss.org Find more HIMSS23 conference coverage here Friday, April 21, 2023 - 22:45

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Synoptic Reporting Improves Pretreatment CT for Advanced Ovarian Cancer

Imaging Technology

An ovarian cancer synoptic report increased completeness of reporting, facilitating referrer communication and having the potential to improve clinical decision-making,” wrote first author Pamela Causa Andrieu, MD , from the department of radiology at Memorial Sloan Kettering Cancer Center in New York City. “An Andrieu et al.’s

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Biomarker model predicts breast cancer risk without racial bias

AuntMinnie

The investigators used patient demographic data taken from electronic medical records and identified instances of cancer from a regional tumor registry. Senior author Constance Lehman, MD, PhD, of Harvard Medical School in Boston said the team is poised to translate these findings into improved clinical care for patients.

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Predictions for Healthcare AI Entering 2023

Aidoc

Whether it be unleashing genomic sequencing to personalize oncologic treatments or developing an electronic medical records system, the healthcare industry as a whole abides by the highest standards of testing and evaluation prior to welcoming novel solutions that may impact patient lives.