Tag: Data analysis
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Weekly digest 42
in Digestactive reading, assessment validity, Canadian Physiotherapy Association, Chartered Society of Physiotherapy, CSP, Data analysis, editors, Founders Lecture, information overload, luggage, manifesto, note-taking, OpenAI voice mode, promotion, promotion application, social work, validity, wikipedia, workshopA weekly collection of things I found interesting, thought-provoking, or inspiring. It’s almost always about higher education, mostly technology, and usually AI-related.
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MyRA for qualitative data analysis
MyRA is a tool for AI-supported qualitative data analysis. It’s currently in beta.
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Generative AI for research – Stellenbosch University physiotherapy division
Generative AI systems like ChatGPT and Claude are rapidly improving next-word predictors capable of generating multimodal content. They share similarities with humans, including biases and hallucinations. Treating GenAI as an expert research assistant for idea generation, literature review, writing, and data analysis requires critical evaluation of outputs.
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BIP AI – AI in research: Opportunities and challenges
In this Blended Intensive Programme on AI, Guillem Jabardo and I explore the potential of generative AI to support all stages of the research process. However, while extremely powerful, these tools still have limitations, necessitating critical review. The ability of generative AI to augment human cognition represents a paradigm shift for academia.
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AI for research – African Doctoral Academy
I gave this presentation on AI in research for participants at the African Doctoral Academy. I highlighted the fact that generative AI as a sophisticated tool that predicts text and generates coherent multimodal content. The presentation discussed AI’s potential in roles like idea generation and data analysis, its current limitations like bias, and emphasised the…
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Are you ready? Here is all the data Facebook and Google have on you
Google offers an option to download all of the data it stores about you. I’ve requested to download it and the file is 5.5GB big, which is roughly 3m Word documents. This link includes your bookmarks, emails, contacts, your Google Drive files, all of the above information, your YouTube videos, the photos you’ve taken on…
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Split learning for health: Distributed deep learning without sharing raw patient data
Can health entities collaboratively train deep learning models without sharing sensitive raw data? This paper proposes several configurations of a distributed deep learning method called SplitNN to facilitate such collaborations. SplitNN does not share raw data or model details with collaborating institutions. The proposed configurations of splitNN cater to practical settings of i) entities holding…
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a16z Podcast: Revenge of the Algorithms (Over Data)… Go! No?
in AIAn interesting (and sane) conversation about the defeat of AlphaGo by AlphaGo Zero. It almost completely avoids the science-fiction-y media coverage that tends to emphasise the potential for artificial general intelligence and instead focuses on the following key points: Go is a stupendously difficult board game for computers to play but it’s a game in…
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Ontario is trying a wild experiment: Opening access to its residents’ health data
This has led companies interested in applying AI to healthcare to find different ways to scoop up as much data as possible. Google partnered with Stanford and Chicago university hospitals to collect 46 billion data points on patient visits. Verily, also owned by Google’s parent company Alphabet, is recruiting 10,000 people for its own long-term…
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The Desperate Quest for Genomic Compression Algorithms
While it’s hard to anticipate all the future benefits of genomic data, we can already see one unavoidable challenge: the nearly inconceivable amount of digital storage involved. At present the cost of storing genomic data is still just a small part of a lab’s overall budget. But that cost is growing dramatically, far outpacing the…
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Eagle-eyed machine learning algorithm outdoes human experts — ScienceDaily
“Human detection and identification is error-prone, inconsistent and inefficient. Perhaps most importantly, it’s not scalable,” says Morgan. “Newer imaging technologies are outstripping human capabilities to analyze the data we can produce.” Source: Eagle-eyed machine learning algorithm outdoes human experts — ScienceDaily The point here is that data is being generated faster than we can analyse…
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Medical images: the only photos not in the cloud – AI Med
We know that AI could prove highly beneficial for radiologists by cutting down on read times and improving accuracy. In addition, AI could be a strong resource for mining large data sets for both individual patient care and global insights. But first, we must access the images. Today’s traditional hardware, CDs, and PACS (picture archiving…
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Mixed methods research: John Cresswell seminar
For me, mixed methods research (MMR) is about using qualitative and quantitative data to strengthen an argument that is difficult to support with only one type of data. It’s about bringing together the numbers (quantitative) and stories (qualitative) to gain a more complete understanding of the world (research problems and questions). We often think of…