It is not about AI, it is about humans. Responsibility gaps and medical AI by Giubilini, A

“…A lot of the language we use to refer to AI, including in healthcare, uses terminology that originally and literally applies to humans and human relationships. …”

Understanding value and the value of understanding in AI medical decision support systems by Brown, RCH

Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis by Zhang, Shao, Yu, Jianing, Xu, Xuhai, Yin, Changchang, Lu, Yuxuan, Yao, Bingsheng, Tory, Melanie, Padilla, Lace M., Caterino, Jeffrey, Zhang, Ping, Wang, Dakuo

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Clinical outcomes of patients with unsuccessful mechanical thrombectomy versus best medical management of medium vessel occlusion stroke in the middle cerebral artery territory by Faizy, TD, Yedavalli, V, Salim, HA, Lakhani, DA, Musmar, B, Adeeb, N, Essibayi, MA, Daraghma, M, El Naamani, K, Henninger, N, Sundararajan, SH, Kuhn, AL, Khalife, J, Ghozy, S, Scarcia, L, Yeo, LL, Tan, BY, Regenhardt, RW, Heit, JJ, Cancelliere, NM, Rouchaud, A, Fiehler, J, Sheth, SA, Puri, AS, Dmytriw, AA

“…Background: Current randomized controlled trials are investigating the efficacy and safety of mechanical thrombectomy (MT) in patients with medium vessel occlusion (MeVO) stroke. Whether best medical management (MM) is more efficient than unsuccessful vessel recanalization during MT remains unknown. …”

Beyond ideals: why the (medical) AI industry needs to motivate behavioural change in line with fairness and transparency values, and how it can do it by Liefgreen, A, Weinstein, N, Wachter, S, Mittelstadt, B

Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities by Koh, Vivian Ci Ai, Ang, Yi Yang, Ser, Wee, Tan, Rex Xiao

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medTrack : a medication and appointment adherence system by Tan, Felice Yu Ting

“…Building on the Amazon Echo Show, medTrack (a medication and appointment adherence system) aims to tackle on this issue through reminding the patient of their medication and appointment schedule at the designated time. …”
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3D deep learning on medical images : a review by Singh, Satya P., Wang, Lipo, Gupta, Sukrit, Goli, Haveesh, Padmanabhan, Parasuraman, Gulyás, Balázs

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Wavelet-based compression of medical images: Filter-bank selection and evaluation by Saffor, A., Bin Ramli, A.R., Ng, K.H.

“…However, no systematic study has been performed to evaluate the coding performance of wavelet filters on medical images. We evaluated the best types of filters suitable for medical images in providing low bit rate and low computational complexity. …”

The impact of death and dying on the personhood of medical students : a systematic scoping review by Ho, Chong Yao, Kow, Cheryl Shumin, Chia, Joshua Chin Howe, Low, Jia Ying, Lai, Melvin Yong Hao, Lauw, Sarah-Kei, How, Ashley Ern Hui, Tan, Lorraine Hui En, Ngiam, Lisa Xin Ling, Chan, Natalie Pei Xin, Kuek, Joshua Tze Yin, Nur Haidah Ahmad Kamal, Chia, Jeng Long, Ahmad Hanifah Marican Abdurrahman, Chiam, Min, Ong, Yun Ting, Chin, Annelissa Mien Chew, Toh, Ying Pin, Mason, Stephen, Krishna, Lalit Kumar Radha

“…Better understanding of how medical students respond to death and dying will inform educationalists and clinicians on how to best support them. …”
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Medical image analysis for eye disease by Liang, Zi Yang.

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Self-learning shape recognition in medical images by Ma, Jingting

“…A massive amount of medical image data, e.g. from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), is generated from hospitals every day. …”
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Barriers and opportunities for WHO ‘best buys’ non-communicable disease policy adoption and implementation from a political economy perspective: a complexity systematic review by Loffreda, G, Arakelyan, S, Bou-Orm, I, Holmer, H, Allen, LN, Witter, S, Ager, A, Diaconu, K

An overview on effectiveness of activation functions in processing medical images by Al-Shoukry, Suhad, Zalili, Musa

“…The Main results contribute how to select best activation functions that suits most accurate and efficient medical image classification basedon this overview, any researcher can choose best activation function after reading this overview.…”
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Development of an AI solution for surgical gauze management by Ang, Soon Kim

“…Gossypiboma/textiloma is an avoidable medical complication caused by human error. It has been inferred to be under reported due to the medicolegal nature of the situation with cases reported only for insurance claim. …”
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Multicenter double-blind study evaluating AI-driven detection of proximal deep vein thrombosis by Curry, N, Allen, E, Silsby, L, Goodacre, S, Deane, C, Deary, A, Foster, A, Griffiths, J, Sharma, R, Thomas, H, Mischewitz, S, Al-Noor, F

Medical tourism in South East Asia: Science mapping of present and future trends by Muhammad Ashraf, Fauzi, Norhana, Mohd Aripin, Nur Sofia Nabila, Alimin, Ting, Irene Wei Kiong, Wider, Walton, Siti Sarah, Maidin, Zainul-Abideen, Ahmed Yousif Abbas

“…Originality/value: This study fills the gap by performing a bibliometric approach to reviewing medical tourism in Southeast Asia using a science mapping technique. …”
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Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…Objective: Neonates’ physiological immaturity and complex dosing requirements heighten their susceptibility to medication administration errors (MAEs), with the potential for severe harm and substantial economic impact on healthcare systems. …”
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Computational Design And Synthesis Of Potential Ns2b-Ns3 Dengue Protease Inhibitors by Salin, Nurul Hanim

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Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention by Orzikulova, Adiba, Xiao, Han, Li, Zhipeng, Yan, Yukang, Wang, Yuntao, Shi, Yuanchun, Ghassemi, Marzyeh, Lee, Sung-Ju, Dey, Anind K, Xu, Xuhai

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