Zobrazeno 1 - 10
of 1 920
pro vyhledávání: '"P. Asiedu"'
Autor:
Olatunji, Tobi, Nimo, Charles, Owodunni, Abraham, Abdullahi, Tassallah, Ayodele, Emmanuel, Sanni, Mardhiyah, Aka, Chinemelu, Omofoye, Folafunmi, Yuehgoh, Foutse, Faniran, Timothy, Dossou, Bonaventure F. P., Yekini, Moshood, Kemp, Jonas, Heller, Katherine, Omeke, Jude Chidubem, MD, Chidi Asuzu, Etori, Naome A., Ndiaye, Aimérou, Okoh, Ifeoma, Ocansey, Evans Doe, Kinara, Wendy, Best, Michael, Essa, Irfan, Moore, Stephen Edward, Fourie, Chris, Asiedu, Mercy Nyamewaa
Recent advancements in large language model(LLM) performance on medical multiple choice question (MCQ) benchmarks have stimulated interest from healthcare providers and patients globally. Particularly in low-and middle-income countries (LMICs) facing
Externí odkaz:
http://arxiv.org/abs/2411.15640
Autor:
Asiedu, Mercy, Tomasev, Nenad, Ghate, Chintan, Tiyasirichokchai, Tiya, Dieng, Awa, Akande, Oluwatosin, Siwo, Geoffrey, Adudans, Steve, Aitkins, Sylvanus, Ehiakhamen, Odianosen, Ndombi, Eric, Heller, Katherine
While large language models (LLMs) have shown promise for medical question answering, there is limited work focused on tropical and infectious disease-specific exploration. We build on an opensource tropical and infectious diseases (TRINDs) dataset,
Externí odkaz:
http://arxiv.org/abs/2409.09201
Autor:
Asiedu, Mercy Nyamewaa, Haykel, Iskandar, Dieng, Awa, Kauer, Kerrie, Ahmed, Tousif, Ofori, Florence, Chan, Charisma, Pfohl, Stephen, Rostamzadeh, Negar, Heller, Katherine
Artificial Intelligence (AI) for health has the potential to significantly change and improve healthcare. However in most African countries, identifying culturally and contextually attuned approaches for deploying these solutions is not well understo
Externí odkaz:
http://arxiv.org/abs/2409.12197
Autor:
Pfohl, Stephen R., Cole-Lewis, Heather, Sayres, Rory, Neal, Darlene, Asiedu, Mercy, Dieng, Awa, Tomasev, Nenad, Rashid, Qazi Mamunur, Azizi, Shekoofeh, Rostamzadeh, Negar, McCoy, Liam G., Celi, Leo Anthony, Liu, Yun, Schaekermann, Mike, Walton, Alanna, Parrish, Alicia, Nagpal, Chirag, Singh, Preeti, Dewitt, Akeiylah, Mansfield, Philip, Prakash, Sushant, Heller, Katherine, Karthikesalingam, Alan, Semturs, Christopher, Barral, Joelle, Corrado, Greg, Matias, Yossi, Smith-Loud, Jamila, Horn, Ivor, Singhal, Karan
Publikováno v:
Nature Medicine (2024)
Large language models (LLMs) hold promise to serve complex health information needs but also have the potential to introduce harm and exacerbate health disparities. Reliably evaluating equity-related model failures is a critical step toward developin
Externí odkaz:
http://arxiv.org/abs/2403.12025
Autor:
Asiedu, Mercy, Dieng, Awa, Haykel, Iskandar, Rostamzadeh, Negar, Pfohl, Stephen, Nagpal, Chirag, Nagawa, Maria, Oppong, Abigail, Koyejo, Sanmi, Heller, Katherine
With growing application of machine learning (ML) technologies in healthcare, there have been calls for developing techniques to understand and mitigate biases these systems may exhibit. Fair-ness considerations in the development of ML-based solutio
Externí odkaz:
http://arxiv.org/abs/2403.03357
Autor:
Mannhardt, Niklas, Bondi-Kelly, Elizabeth, Lam, Barbara, Mozannar, Hussein, O'Connell, Chloe, Asiedu, Mercy, Buendia, Alejandro, Urman, Tatiana, Riaz, Irbaz B., Ricciardi, Catherine E., Agrawal, Monica, Ghassemi, Marzyeh, Sontag, David
Large language models (LLMs) have immense potential to make information more accessible, particularly in medicine, where complex medical jargon can hinder patient comprehension of clinical notes. We developed a patient-facing tool using LLMs to make
Externí odkaz:
http://arxiv.org/abs/2401.09637
Autor:
Hegselmann, Stefan, Parziale, Antonio, Shanmugam, Divya, Tang, Shengpu, Asiedu, Mercy Nyamewaa, Chang, Serina, Hartvigsen, Thomas, Singh, Harvineet
A collection of the accepted Findings papers that were presented at the 3rd Machine Learning for Health symposium (ML4H 2023), which was held on December 10, 2023, in New Orleans, Louisiana, USA. ML4H 2023 invited high-quality submissions on relevant
Externí odkaz:
http://arxiv.org/abs/2312.00655
Autor:
Lambon-Quayefio, Monica, Yeboah, Thomas, Owoo, Nkechi S., Petreski, Marjan, Koranchie, Catherine, Asiedu, Edward, Zakaria, Mohammed, Berko, Ernest, Agyemang, Yaw Nsiah
Ghana-s current youth unemployment rate is 19.7%, and the country faces a significant youth unemployment problem. While a range of youth-employment programs have been created over the years, no systematic documentation and evaluation of the impacts o
Externí odkaz:
http://arxiv.org/abs/2311.06048
Autor:
Sirko, Wojciech, Brempong, Emmanuel Asiedu, Marcos, Juliana T. C., Annkah, Abigail, Korme, Abel, Hassen, Mohammed Alewi, Sapkota, Krishna, Shekel, Tomer, Diack, Abdoulaye, Nevo, Sella, Hickey, Jason, Quinn, John
Mapping buildings and roads automatically with remote sensing typically requires high-resolution imagery, which is expensive to obtain and often sparsely available. In this work we demonstrate how multiple 10 m resolution Sentinel-2 images can be use
Externí odkaz:
http://arxiv.org/abs/2310.11622
Autor:
Joseph Humphrey Kofi Bonney, Deborah Pratt, Magdalene Ofori, Takaya Hayashi, Abigail Abankwa, Yaw Awuku-Larbi, Selassie Kumordjie, Bright Agbodzi, Musah Salisu, Ama Amankwa Ofosua Mante, Stella Bour, Miriam Eshun, Juliana Naa Dedei Acquah Amaning, Prince Ketorwoley, Nancy Enimil, Joel Koomson, Gertrude Stephens, Franklin Asiedu-Bekoe, Dennis Laryea, Samuel Dadzie, Toshihiko Suzuki
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-7 (2024)
Abstract Background Viral hemorrhagic fevers (VHFs) belong to a group of viral infectious diseases that interfere with the blood’s clotting mechanism. VHF has a wide host range, including bats, rodents, or arthropods such as mosquitoes and ticks. M
Externí odkaz:
https://doaj.org/article/f171f9ea3c4141df83a60185fe8f063d
