https://www.aicollective.co/blog daily 0.75 2022-12-12 https://www.aicollective.co/blog/welcome-to-the-ai-collective monthly 0.5 2020-12-06 https://www.aicollective.co/blog/ai-covid-and-wearables monthly 0.5 2021-05-05 https://www.aicollective.co/blog/viral-dalton monthly 0.5 2021-05-12 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1620776131897-1JDJPYC6XRDEOG7IS2W8/unnamed+%283%29.png Blog - Friends of AI Collective: Story Series - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1620775977288-WPNDCDK7DN093KZ4Y3O4/unnamed.png Blog - Friends of AI Collective: Story Series - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1620776217572-DL8FYAQ94XQLXE29E5TO/unnamed+%285%29.png Blog - Friends of AI Collective: Story Series - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1620776027802-T8OJRJAZGJM1G11VOYDY/unnamed+%281%29.png Blog - Friends of AI Collective: Story Series - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1620776085806-A0KNY0BPF990TIR9C3G3/unnamed+%282%29.png Blog - Friends of AI Collective: Story Series - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1620776164307-WSX4D5LIEZUDFZ6GNBIV/unnamed+%284%29.png Blog - Friends of AI Collective: Story Series - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://www.aicollective.co/social-icons-1 daily 0.75 2020-11-19 https://www.aicollective.co/social-icons-1/linkedin-r5aj7 monthly 0.5 2020-11-02 https://www.aicollective.co/social-icons-1/linkedin-r5aj7-r92eb monthly 0.5 2020-11-19 https://www.aicollective.co/social-icons_whitley daily 0.75 2020-11-02 https://www.aicollective.co/social-icons_whitley/linkedin monthly 0.5 2020-11-02 https://www.aicollective.co/podcasts daily 0.75 2023-06-08 https://www.aicollective.co/podcasts/explainability monthly 0.5 2023-06-07 https://www.aicollective.co/podcasts/teaser monthly 0.5 2023-01-25 https://www.aicollective.co/podcasts/image-recognition monthly 0.5 2023-06-13 https://www.aicollective.co/about daily 0.75 2021-02-21 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1605484021843-NWMKATN6YKJJ1OKICVEB/unnamed+%281%29.jpg About https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1605482927536-EGBRSPQ7AOXSJATGR2AO/Cheung%2C+Christy+%28Headshot%29.jpg About https://www.aicollective.co/roadmap-overview daily 1.0 2021-06-29 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1606786443752-MRSVNTVW3ILKWZFL7PPI/photo-1554224673-39c3202f6816.jpg Roadmap Overview - Part I: Start Here If the terms ‘artificial intelligence,' ‘machine learning,’ or ‘algorithms’ seem like another language to you, you are not alone. These are common buzzwords seen almost everywhere now, but what do they really mean? Here we offer a high level overview of AI from a healthcare perspective, where it came from, and how it fits in with what you already know. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1606787148649-5VV29FEJED8400SHF77C/eleventh-wave-JsjtrixOiWc-unsplash.jpg Roadmap Overview - Part I: The Framework What is an AI model? From a clinical perspective, it is helpful to first think about models as being composed of 3 major components: The type of inputs (or data) that go into the model. The model’s algorithm(s) The type of output (or inference the model makes) https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1605131122862-AJ24GOYYEZUI6RO2ZRCN/markus-spiske-qjnAnF0jIGk-unsplash.jpg Roadmap Overview - Part I: Input It’s all about the data…. Many types of data can be used in a model, including unstructured data such as images or natural language, as well as structured, or tabular data. The ability to look at unstructured data is a major distinction between machine learning and basic statistical analytics. However, machine learning usually still involves considerable data pre-processing, and often the data are transformed from one form to another. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1605131226384-K9WNHJSO9AFZUEOB3L1S/lenin-estrada-OI1ToozsKBw-unsplash.jpg Roadmap Overview - Part I: Algorithm Learning Styles When we talk about algorithms, there are two main things to consider: the learning style and the algorithm “type.” We will talk about learning styles first, which is a way to describe how the algorithm uses data to gain information. There are four major learning styles — supervised, unsupervised, semi-supervised, and reinforcement. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1605131452713-WOIWRMYECN0J07OEDP1A/uriel-sc-11KDtiUWRq4-unsplash.jpg Roadmap Overview - Part I: Algorithm Types There are numerous types of machine learning algorithms. While we will not go into depth on the topic at this time, we do want to mention a few of the most common ones you may see — neural networks, support vector machine, decision trees, and naive Bayes. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1606786727488-D7RVSKDH9SAPT1509QFO/image-asset.jpeg Roadmap Overview - Part I: Output When we think about the output of the model, it all depends on how the model was designed to provide information. It can do this in many ways. If a model is a classifier, it might be designed to classify multiple elements or only one element. For example, if a binary model were designed to determine if an image contained a dog, the model will only provide one of two outputs — “yes” or “no.” https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1605131722455-RHP1XLR7V734M7XV16T8/national-cancer-institute-cQ8FfVNvbew-unsplash.jpg Roadmap Overview - Part II: AI in Healthcare While we have touched on a lot of information about AI models, ultimately, how can you start applying this knowledge to help you sift through all the news and data about emerging AI tools and applications in healthcare? How do we go about gaining a high level understanding of the potential clinical utility of a model? https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1611086022112-Y7I0SX0J4BGFOAA5VVDD/frederic-koberl-x_0hW-KaCgI-unsplash.jpg Roadmap Overview - Part III: Policy, Regulations, And Standards The disruptive potential of artificial intelligence and the role it should play within healthcare are issues that governments and organizations alike are grappling over how to handle. Regardless of the industry, we have to ensure that regulations are in place to guide the creation, and subsequent deployment, of AI models. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1611760551703-1H8OBQYUU430XMFRH4H9/bud-helisson-kqguzgvYrtM-unsplash.jpg Roadmap Overview - Part III: Aligning on a Vision and Purpose When we look at the global conversations around AI taking place among governments and the private sector, there is a lack of clarity and consistency on what the guiding principles should be for lawmakers, researchers, and businesses. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1612919007833-U9LCU8HEVJTRVO0MVEDE/scott-graham-OQMZwNd3ThU-unsplash.jpg Roadmap Overview - Part III: Creating A Strategy The "Guidance for Regulation of Artificial Intelligence Applications" draft rule lists key considerations for other government agencies when creating AI regulation.² Among the top considerations are the need to promote public trust in AI and to minimize or eliminate regulation where possible. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1613529250885-GYALU6BGTNVSJQB9805T/kelly-sikkema-1gWlUC43MGY-unsplash.jpg Roadmap Overview - Part III: Putting Regulation in Place With any new technology, unintended consequences are bound to occur and the stewardship of that technology includes vigilance and active surveillance to identify signals of a potentially undesirable impact. This is a reason why diversity and representation is so critical within AI. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1614184215645-WUBDOIZV8RRN2LKLJ8OP/federico-beccari-ahi73ZN5P0Y-unsplash.jpg Roadmap Overview - Part III: A Shared Language Even if all the necessary policies and regulations existed, it is still not enough for a given field to advance and mature. This is where standards come into play. Standards play a fundamental role in everyday life and are necessary to ensure the quality, safety, and functionality of almost everything we interact with in our daily lives. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1623210081423-JWUR8XM22EQFRF2SLN18/unsplash-image-N7FtpkC_P7o.jpg Roadmap Overview - Part IV: Why Transparency Matters At what point can a machine be trusted to make important decisions? As George E.P. Box said, “All models are wrong, but some are useful.” It is imperative that we know how a model could be wrong in order to minimize risk. If we do not know how a model came to the conclusion it did, then we do not know when it is or is not appropriate to use, or when it will or will not be useful. https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1624421947570-IZNRRYO7M2JF7GYP95KX/unsplash-image--Rc6usOigMk.jpg Roadmap Overview - Part IV: Interpretability vS. Explainability Not all models are interpretable (i.e. intuitively understandable). Therefore, we need another way to try to make sense of them, and that is where explainability comes into play. Can we explain a complex model by breaking it down into smaller parts that are each simple enough to be interpretable? https://www.aicollective.co/ai-introduction daily 0.75 2021-01-20 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1605014869253-N78O0820SB4KEB6JV30H/7vx.jpg AI Introduction https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1605013493538-FFOR7CG0OP1IF0RTREIL/9ln3ztv.jpg AI Introduction https://www.aicollective.co/starting-with-a-framework daily 0.75 2021-01-20 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1603194593780-MSQLE2VNSZNLKDD9V36D/Design%26Deployment.png Starting with a Framework In this image, the value of an AI application is broken down into its theoretical value, which is defined here as the model’s ability to accurately generate the output it was designed to provide, and its contextual value, which is defined as the clinical impact of the model when integrated into a complex clinical workflow and environment. https://www.aicollective.co/its-all-about-data daily 0.75 2021-01-20 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1602527340123-WHQUPQJ9VRFZHV3ZGFD2/unnamed.png It is All About Data Detecting fraud — Each image repesents the summation of mouse movements on the computer screen, utilizing color to represent acceleration and direction. These unique patterns are able to help detect behavior patterns associated with fraudulent activity¹. https://www.aicollective.co/how-do-machines-learn daily 0.75 2021-01-20 https://www.aicollective.co/types-of-algorithms daily 0.75 2021-01-20 https://www.aicollective.co/output-of-ai-algorithms daily 0.75 2020-12-06 https://www.aicollective.co/ai-in-healthcare daily 0.75 2021-01-20 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1602530579441-MLFNS2M62Z41VMYQ96KQ/unnamed+%281%29.png AI in Healthcare From the IQVIA Report "The Changing Landscape of Research and Development," April 2019 (Advanced Analytics models simply refer to Machine Learning models) https://www.aicollective.co/resources daily 0.75 2021-03-05 https://www.aicollective.co/policy-regulations-and-standards daily 0.75 2021-02-17 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1606959994076-9LZ6ZSULABVJS7S7AOYQ/rId15_image5.png Policy, Regulations, and Standards https://www.aicollective.co/aligning-on-a-vision-purpose-for-ai daily 0.75 2021-02-17 https://www.aicollective.co/creating-a-strategy daily 0.75 2021-02-17 https://www.aicollective.co/putting-regulation-into-place daily 0.75 2021-02-24 https://www.aicollective.co/a-shared-language daily 0.75 2021-02-24 https://www.aicollective.co/media daily 0.75 2022-12-11 https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1615930321354-9KRIIBA3B4AY824MACWW/Pharma+Equinox+Magazine-4.png Media https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1615930300086-X053WM9DVBSRZ0R7B4UK/Pharma+Equinox+Magazine-3.png Media https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1615930273659-1TZPNWVBS7VR21VAN6A4/Pharma+Equinox+Magazine-2.png Media https://images.squarespace-cdn.com/content/v1/5f7e48f8c8aeda1ce7a0eeb4/1615930220301-XKTTYU5ONW7XSW1CVP1U/Pharma+Equinox+Magazine-1.png Media https://www.aicollective.co/transparency-matters daily 0.75 2021-06-10 https://www.aicollective.co/interpretability-explainability daily 0.75 2021-06-28